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488 stories, newest first, oldest shown from October 7, 2026. Rebuilt just now.

AdaptTok-Indic: Script-Aware Adaptive Tokenization for Indic LanguagesarXiv:2610.33017v1 Announce Type: new Abstract: Multilingual tokenizers trained on English-dominated corpora often over-segment Indic languages, resulting in longer token sequences and increased tokenization disparity across…
Conceptizer: Next-Token Prediction Is Not All You NeedarXiv:2610.33027v1 Announce Type: new Abstract: Next-token prediction (NTP) rewards only the token that occurs next, penalizing every alternative. But natural language often offers many ways to express the same meaning. We…
Entity-Aware Evaluation of OCR Systems for Historical Document TranscriptionarXiv:2610.33004v1 Announce Type: new Abstract: Optical Character Recognition (OCR) is essential for digitizing historical archives, yet standard evaluation metrics such as Character Error Rate (CER) do not necessarily reflect…
From Writing Advice to Manuscript Governance: A Constrained-Transformation Framework for Academic RevisionarXiv:2610.33001v1 Announce Type: new Abstract: Academic revision presents a governance problem when legitimate writing objectives conflict. Writing-process and social-science research show that revision is recursive and that…
Knowledge-Guided LLM for Intent-Driven Service Orchestration in Integrated Terrestrial and Non-Terrestrial 6G NetworksarXiv:2610.33007v1 Announce Type: new Abstract: Natural-language service intents in integrated terrestrial and non-terrestrial (TN/NTN) 6G networks can be incomplete, ambiguous, or inconsistent, making unconstrained LLM…
Linear-Time Context Compression with State-Space EncodingarXiv:2610.33006v1 Announce Type: new Abstract: Transformer-based large language models (LLMs) impose substantial computation and memory costs as context sizes increase, motivating methods that compress a context into a shorter…
Merge-Based Vocabulary Extension Stalls at the Pre-Tokenizer: An English-Preserving Repair for Nepali, Tested in Continued PretrainingarXiv:2610.33016v1 Announce Type: new Abstract: Llama-3, Qwen3 and many other open LLMs pre-tokenize text with a regular expression whose word class admits only Unicode letters. Devanagari vowel signs are combining marks, so this…
Mine or Yours? Mind-Bridged Language Models Take Each Other's Memories as Their OwnarXiv:2610.33020v1 Announce Type: new Abstract: If your brain were connected directly to someone else's, would you still know which thoughts were yours? We build a functional version with two copies of one language model: each…
OpenESM: Energy-Steered Models Are Scalable Foundation LearnersarXiv:2610.33005v1 Announce Type: new Abstract: Energy-based models have shown promising properties for domain-specific tasks but remain challenging in modeling general-purpose scenarios. To bridge this gap, we design…
Recursive Semantic Divergence for LLM Agent ConsistencyarXiv:2610.33012v1 Announce Type: new Abstract: Large Language Model (LLM) agents with tool use exhibit inconsistent behavior across independent runs from identical states, calling different tools, producing contradictory…
SLICE-Mem: Salience-Gated Lightweight Information Curation for Efficient LLM Agent MemoryarXiv:2610.33015v1 Announce Type: new Abstract: Long-term memory enables large language model (LLM) agents to maintain personalized and temporally coherent interactions, but repeated LLM inference for memory admission…
SUDO: From Scientific Publications to Global Scholarly DiscoursearXiv:2610.33018v1 Announce Type: new Abstract: Scholarly Knowledge Graphs (SKGs) support literature search, scientific discovery, and agent-assisted research. Yet, most approaches to SKG construction pre-specify the knowledge…
The Social World Model Evaluation GaparXiv:2610.33014v1 Announce Type: new Abstract: A negotiation assistant can reach a good deal without accurately predicting the other person's response. We ask whether evaluations of social world models test that prediction…
TraceQuery: learning what to recompute from full-denoising trajectory in diffusion language modelsarXiv:2610.33008v1 Announce Type: new Abstract: Diffusion large language models (dLLMs) enable flexible generation through iterative masked denoising, but incur substantial inference cost because token representations are…
Whispering Wisely: Smart Subset Selection for ASR Fine-TuningarXiv:2610.32997v1 Announce Type: new Abstract: Automatic Speech Recognition (ASR) models such as OpenAIs Whisper have substantially improved speech recognition quality but remain expensive to fine-tune, especially when large…
OpenAI announces three big science discoveries and a new way to work with academicsLess than a month after its mass release of hundreds of manuscripts that it said contained solutions to long-standing mathematics questions, OpenAI is back with three more "major" discoveries in math, computer science, and…
Will the real Anthropic please stand upThis story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first, sign up here. After weeks of frenzied speculation, Anthropic has filed its IPO prospectus. The 335-page…
Anthropic is burning gas to feed the AI boomAs it prepares to go public, Anthropic's S-1 filing makes generative AI's methane dependency glaringly obvious. "Competition for access to electrical supply and data center locations with adequate power availability is intense."…
The RealReal won’t let AI agents hog designer clothingThe RealReal, a secondhand luxury fashion consignment retailer, said it's updating its bot defense system, effectively making it harder for AI agents to shop on its site. The change comes days after The Verge reported that an AI…
Five weird details from Anthropic’s IPO filingAnthropic has finally filed its S-1 prospectus with the SEC, a document designed to give investors a look under the hood of its business, from how much its executives are making and plans for spending its IPO billions to the…
The Download: everyday AI harms and the race to nuclear spaceflightThis is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology. Opinion: The focus on AI safety disasters ignores everyday harms —Sam Hiner, cofounder of…
Microsoft offers buyouts to 60,000 employeesMicrosoft is offering voluntary buyouts to up to 60,000 employees across the US, UK, Canada, and India. In a message to employees, Microsoft chief people officer Amy Coleman writes that this gives staff members "the opportunity…
Anthropic’s IPO filing lays out a plan to ‘revolutionize every area of human endeavor’ with AIAnthropic has filed its S-1 prospectus with the Securities and Exchange Commission, preparing the company behind Claude to beat OpenAI to the punch with an IPO. In a filing with the SEC, Anthropic said it plans to list on the…
Kevin Roose is AGI-pilled. Why aren’t you?Today, I’m talking to Kevin Roose, journalist and author of the new book The AGI Chronicles, which details the recent and explosive transformation of the AI industry. Kevin was a longtime New York Times reporter and host of the…
Can AI help solve the COBOL code crisis?What do the IRS, banks, airlines, and government infrastructure around the world have in common? They're all running on systems propped up by antique computer code that nobody dares touch, lest everything come crashing down…
The focus on AI safety disasters ignores everyday harmsConsider what passes for success in technology policy. An AI company promises that its chatbot will not encourage suicide. A social media platform makes it more difficult for children to buy fentanyl. These are important…
An Agentic Approach with Evidence-Grounded Verification for Multimodal Emotion Reasoning in ConversationarXiv:2610.31685v1 Announce Type: new Abstract: LLM-based multimodal emotion reasoning systems perform well on standard benchmarks, but improving them through instruction tuning can be computationally expensive. Agentic pipelines…
Distributional Alignment of LLMs and Its Generalization PropertiesarXiv:2610.31687v1 Announce Type: new Abstract: Large language models are increasingly used to simulate and probe human behavior, e.g., for surveys. For these applications, a key property is that outputs satisfy distributional…
Free Lunch for LLMs Confidence: The RL Critic Already KnowsarXiv:2610.31820v1 Announce Type: new Abstract: Reliable confidence estimation is essential for trustworthy deployment of large language models (LLMs), but dedicated confidence training stage requires additional data and compute…
From Target Selection to Condition Reuse: Auditing Residual Interventions in Tool-Use ModelsarXiv:2610.31686v1 Announce Type: new Abstract: Activation interventions can make a language model produce a target answer, but can the model use the intended condition in other computations? We study this question in Qwen3.5-27B…
Knowledge Graphs Quality Assessment in the Era of LLMs: A Conceptual FrameworkarXiv:2610.31684v1 Announce Type: new Abstract: Knowledge Graphs (KGs) have been popularized during the last few decades and are increasingly constructed and consumed by Large Language Models (LLMs). Various applications…
LAMB: A Modern Contextual Language Model for LatinarXiv:2610.31723v1 Announce Type: new Abstract: This article introduces Latin Modern BERT (LAMB), an encoder for the Latin language based on the ModernBERT architecture, pretrained in two phases on more than 74B Latin tokens…
Latent Coherence: Do Frontier Language Models' Probability Judgments Obey the Law of Total Probability?arXiv:2610.31833v1 Announce Type: new Abstract: LawZero's Scientist AI trains a Predictor toward the Bayesian posterior, with an objective that penalizes inconsistent probabilities among latent explanations. We ask whether…
MisconceptDialogue: Evaluation Criteria Shape Measured Success in LLM Math TutoringarXiv:2610.31679v1 Announce Type: new Abstract: Large language models are increasingly used as math tutors, raising two questions: can a single LLM detect a student's error, diagnose the underlying misconception, and remediate it…
Multi modal perceived conversation success prediction for spontaneous autistic and non-autistic dyadic interactionsarXiv:2610.31682v1 Announce Type: new Abstract: Conversation success is important for communication, social bonds, and well-being and is often reduced in autistic-neurotypical conversations. Previous studies have predicted…
Rethinking Structured Generation: Can Graph-Based Reasoning Resolve Ambiguity?arXiv:2610.31681v1 Announce Type: new Abstract: Structured generation is typically formulated as a deterministic mapping from input to a single structured output. This assumption is fundamentally misaligned with natural language…
SAGE: Sense-Aligned Multimodal Grounding Evaluation with Gloss-Augmented ReasoningarXiv:2610.31838v1 Announce Type: new Abstract: This paper introduces Sense-Aligned Grounding Evaluation (SAGE), a unified 10-candidate image-selection benchmark that reformulates VWSD, VerSe, and WikiDiverse into a shared…
SPECMEM: Accelerating Agentic Tool Calling via Live Memory ManagementarXiv:2610.31840v1 Announce Type: new Abstract: Tool-calling agents are mostly optimized for accuracy; in deployment, however, their growing cost is latency: every tool call is decoded autoregressively. Speculative decoding…
The Schema Coherence Inventory: Measuring Whether an Assigned Belief Organizes a Language Model's CognitionarXiv:2610.31683v1 Announce Type: new Abstract: Persona-conditioned language models are used as simulated patients and affective agents, but there is no validated way to ask whether a belief assigned to such a model organizes its…
Validating the Comparison, Not Just the Scorer: Why Overall Accuracy Can Mislead in Interactive LLM EvaluationarXiv:2610.31678v1 Announce Type: new Abstract: Many LLM studies compare how models respond to different follow-up prompts. For example, one prompt may neutrally ask a model to reconsider, while another insists that an invented…
What the Query Remembers: Query Abstraction Governs Lexical and Dense Retrieval of Classical Arabic PoetryarXiv:2610.31821v1 Announce Type: new Abstract: How well a poetry archive can be searched depends on what the user still remembers, not only on what the model understands. We show this for Classical Arabic poetry, benchmarking…
Autoregressive Multimodal Anomaly Detection with Large Language Models for Microservice SystemsarXiv:2610.31722v1 Announce Type: new Abstract: Microservice systems have become a dominant architecture for large-scale cloud applications, enabling rapid deployment and elastic scaling. However, ensuring the reliability and…
Benchmarks Are Surprisingly Compaction-FriendlyarXiv:2610.31778v1 Announce Type: new Abstract: Long horizon agentic tasks are now pushing LLM agents past their context window. To continue the task, the agent scaffold has to free up the context window, a process known as…
Cognitively Constrained Partners for Zero-Shot Coordination in Real-Time Partitioned ControlarXiv:2610.31726v1 Announce Type: new Abstract: Effective human-machine teaming requires agents that coordinate with unpredictable human partners. Reinforcement learning from live human feedback or large behavioural datasets is…
Collaborative In-Context Learning for Indoor Radio Map EstimationarXiv:2610.31702v1 Announce Type: new Abstract: Indoor radio map estimation (RME) is essential for wireless applications such as coverage planning, localization, and network deployment. However, most existing methods follow a…
ConsMSA: Semantic Distribution Consistency Learning for Multimodal Sentiment AnalysisarXiv:2610.31731v1 Announce Type: new Abstract: Multimodal sentiment analysis (MSA) aims to predict human sentiments by integrating signals from different modalities such as text, video, and audio. However, raw multimodal…
CuraLoc: Repository-Level Fault Localization via Planned Code InspectionarXiv:2610.31809v1 Announce Type: new Abstract: A bug report describes what went wrong, but rarely where the code should change. Existing repository-level localization methods often let language models iteratively decide what…
Does LeWorldModel Preserve Local Action Geometry?arXiv:2610.31716v1 Announce Type: new Abstract: We examine how closely pretrained LeWorldModel (LeWM) reproduces the effects of small action changes. Using matched simulator and model responses, we measure action sensitivity with…
Efficient Omni-modal Large Language Model Inference via Per-Query Modality SelectionarXiv:2610.31768v1 Announce Type: new Abstract: Omni-modal large language models (Omni-LLMs) can jointly process a broad range of modalities, such as text, audio, and video, enabling stronger multimodal understanding and…
End-to-End Differentiable Diffusion Conditioning for Physics-Informed OptimizationarXiv:2610.31721v1 Announce Type: new Abstract: Optimizing high-dimensional physical systems under expensive evaluations and complex constraints is a central challenge in science and engineering. In offline model-based…
Learning to Be Monitored: Causal Bounds and Intervention-Aware Post-Training Recipes for Chain-of-Thought MonitorabilityarXiv:2610.31733v1 Announce Type: new Abstract: Chain-of-thought (CoT) monitoring aims to detect potentially harmful behaviors in large language models (LLMs) from their CoTs. Intervention-based evaluations measure this property…
Not All Retained Clients Are Equal: Client Selection for Federated UnlearningarXiv:2610.31786v1 Announce Type: new Abstract: Federated unlearning (FU) aims to remove a designated target client's influence from a trained model without the prohibitive cost of retraining from scratch. Existing methods…
PaperScorer: How Predictable Is Paper Acceptance?arXiv:2610.31791v1 Announce Type: new Abstract: Automated research is largely evaluated by benchmark performance, but the value of research rarely reduces to a single score. Humans judge a work's holistic contribution through…
The Path to NDE 4.0: A Review of Algorithms, Techniques, and Strategies for Autonomous InspectionarXiv:2610.31704v1 Announce Type: new Abstract: Non-Destructive Inspection (NDI) is a cornerstone of modern quality assurance, critical for ensuring the safety and reliability of infrastructure and manufactured components without…
Towards Adversarially Robust Multigraph Neural Networks for Financial Crime AnalysisarXiv:2610.31718v1 Announce Type: new Abstract: Financial transaction networks are naturally represented as multigraphs, where repeated transactions between the same pair of accounts are modeled as distinct edges. Recently…
When and How Does Muon Precondition? The Role of Structured Gradient NoisearXiv:2610.31728v1 Announce Type: new Abstract: Muon has become a popular optimizer for large language model training, yet its theoretical foundations remain poorly understood. In this work, we study how gradient noise geometry…
r/opensource just banned AI, non-English speakers and moreThe mods at r/opensource posted new submission rules that, among other things, banned projects that use AI. The post made Saturday evening opens by saying, "If your project uses AI, is made by AI, or is intended for AI, it's not…
Blue Planet III is keeping the rough edges in the age of AIBBC's Blue Planet III is looking to prove its authenticity by leaving in the less-than-perfect shots. Previous incarnations of the nature series were defined by their gorgeous, crystal-clear footage that seemed almost too good to…
Pennsylvania will require labels on AI-generated adsOn Thursday, Pennsylvania Governor Josh Shapiro signed the Artificial Intelligence Deceptive Advertising Act into law, requiring disclosures on AI-generated ads. The law requires any ad - whether it's a still image, video, audio…
OpenAI now trains its frontier AI models with no internet accessOpenAI is now training its most advanced AI models without internet access following a string of rogue hacking incidents. In a blog post on Friday, OpenAI says it built an offline testing environment where AI models can interact…
Google’s AI search changes upended online publishingThis is The Stepback, a weekly newsletter breaking down one essential story from the tech world. For more about AI's impact on the web, follow Emma Roth. The Stepback arrives in our subscribers' inboxes on Sunday at 8AM ET. Opt…
Jack Dorsey’s Block made an AI model that talks to you like an awkward new friendJack Dorsey's Block announced an AI model called Dessa that's trained "from scratch on nothing but human conversation," and to show off the model, Block shared chats it has had with humans that can occasionally be a little…
The iPhone Duo should have been an iPadWe gave the iPhone Duo a 7 /10. But that wasn't always the score we planned, and it might not be the right score forever. Such are the challenges of reviewing - and assessing - a big, new idea about the most popular smartphone in…
Now Google says it might use your Gmail and Google Photos data to target adsGoogle has updated its privacy policy in a way that could mean you'll start seeing targeted ads based on your personal data if you're using personalized AI features. The update, spotted by Android Authority, adds an exception to…
The Download: testing six tech promises and biotech’s blind spotsThis is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology. Are we there yet? A reality check on six big tech promises Some seemingly impossible feats…
Meta delays new business terms after publisher pushback on AI scrapingMeta is delaying the enforcement of its new business terms after publishers raised concerns that they could allow the company to scrape news sites for AI training, as reported earlier by Fast Company. In a statement to The Verge…
In the biotech world, you can’t see everythingEarlier this week, I attended a screening of You Can See Everything, the buzzy new documentary about the disgraced former biotech CEO Elizabeth Holmes. I went in not really knowing what to expect. I’d avoided spoilers (and won’t…
Retro gaming is being overrun with AIRetro video games are everywhere lately - especially in places where they aren't supposed to be. Halo in a web browser, Wind Waker on the iPhone, Super Smash Bros. in mixed reality. Over the past month or so, these kinds of…
AQL-Lite: Enabling Efficient Knowledge Acquisition for Arabic LLMs via Data-Centric Continual PretrainingarXiv:2610.30344v1 Announce Type: new Abstract: Training Arabic large language models faces challenges from noisy web data, dialectal variation, and the high cost of continual pretraining (CPT). We introduce AQL-Lite (AQL: Arabic…
Behind Aggregate Scores: What Systematically Varying Arena-Hard's LLM Judge RevealsarXiv:2610.30512v1 Announce Type: new Abstract: LLM judges are used to determine which of two answers is better. Trusting these verdicts requires knowing how repeatable they are and how much they depend on the judge's…
CiteAnchor: Source-Aware Grounding for Hallucinated Citation Detection and ResolutionarXiv:2610.30355v1 Announce Type: new Abstract: Hallucinated citations make it harder to trace sources and verify the evidence behind scientific claims. Detecting them is difficult because bibliographic records can be incomplete…
Climbing the Ladder: Automating Data Pipelines and Reproducing Baselines in Low-Resource SettingsarXiv:2610.30374v1 Announce Type: new Abstract: The massively multilingual translation systems that now include Sicilian learned it from noisy, non-standardised web text. To obtain better translation quality, we redevelop the…
Consistency Is Not Validity: Self-Rewarded Moral Argumentation Makes Language Models Decisive but PliablearXiv:2610.30349v1 Announce Type: new Abstract: LLMs are increasingly consulted for moral judgment. We aim to improve performance on such tasks by rewarding good arguments, on the premise that arguing well increases the…
FusionEval: Benchmarking Model Fusion for Large Language ModelsarXiv:2610.30162v1 Announce Type: new Abstract: Model fusion aims to integrate the capabilities of multi-expert models into a single model. Existing evaluations offer limited coverage of reasoning with long chains of thought and…
Lighthouse: On Building a Trustworthy Digital Assistant for Exploring History with Civil Rights ArchivesarXiv:2610.30158v1 Announce Type: new Abstract: Artificial intelligence (AI), as a decision-support aid, provides new tools for studying history effectively using multimodal data, including text, images, and audio. We present, to…
Measuring Research Progress and Linguistic Inclusion in Low-Resource LanguagesarXiv:2610.30296v1 Announce Type: new Abstract: Large Language Models (LLMs) have accelerated research on low-resource and multilingual NLP, but their effectiveness in creating an equitable landscape remains unmapped. We analyze…
MemPlan: Memory-Conditioned PDDL Planning for Partially Observable Text EnvironmentsarXiv:2610.30379v1 Announce Type: new Abstract: LLM agents are flexible in language interaction, but using them as long-horizon planners is costly and prone to hallucinated or invalid actions. This paper targets a different role…
Protegrity-PII Technical ReportarXiv:2610.30518v1 Announce Type: new Abstract: We present Protegrity-PII, a new PII decision model for structured and unstructured text. Protegrity-PII achieves a typed recall of 0.915 with a precision of 0.907 on a new…
Rethinking the Evaluation of LLM Fact-CheckersarXiv:2610.30504v1 Announce Type: new Abstract: Large language models (LLMs) are widely used to answer factual questions, but their answers can contain errors and must be fact-checked claim by claim. Yet the resulting score…
SIM-UT: A User Simulation based Evaluation Framework for Medical Triage ChatbotsarXiv:2610.30412v1 Announce Type: new Abstract: LLM-based chat agents are increasingly used for complex, multi-turn, multilingual medical triage in low- and middle-income countries (LMICs), yet evaluation methods focus on…
Self-Assessment Reinforcement Learning for Search-State Awareness in Retrieval-Augmented Large Language ModelsarXiv:2610.30435v1 Announce Type: new Abstract: Recent advances in search agents have enabled large language models to tackle complex tasks by retrieving and synthesizing external information. However, existing search agents…
TauIndianBankBench: Procedure-Aware, Action-Oriented Evaluation of Tool-Using Conversational AgentsarXiv:2610.30161v1 Announce Type: new Abstract: Many Indian banks serve customers through FAQ pages and scripted chatbots. Assistants based on language models could respond faster and carry out requests such as blocking a card…
baseVultra: Compact Nonlinear Recurrence with Reallocated CapacityarXiv:2610.30154v1 Announce Type: new Abstract: Nonlinear recurrent networks remain useful for streaming sequence modeling, yet gated cell design is still dominated by LSTM and GRU. We study whether recurrent computation can be…
A Quadratic Lens on Muon's Polar Update: Benefits, Pitfalls, and the Role of Newton-SchulzarXiv:2610.30280v1 Announce Type: new Abstract: Muon updates matrix-valued parameters along approximately orthogonalized directions and often trains large language models faster than AdamW, yet it remains unclear when and why…
Automated screening of privacy risks in medical AIarXiv:2610.30229v1 Announce Type: new Abstract: Medical artificial intelligence (AI) models are often shared without their training data, assuming this protects the patients who contributed them. However, a model can reveal…
Benchmarking Model Compression Techniques Across Heterogeneous Edge Platforms: A Predictive Maintenance Use Case for Rotating MachineryarXiv:2610.30228v1 Announce Type: new Abstract: To enable Industry 5.0, where autonomous systems are widely adopted and integrated with people to promote sustainable development in industries, it is imperative to adapt complex…
Edit, Don't Imitate: Minimal-Edit On-Policy Distillation for Multimodal ReasoningarXiv:2610.30231v1 Announce Type: new Abstract: Visual mathematical reasoning can fail before reasoning begins: when a vision-language model (VLM) misreads a diagram, subsequent reasoning proceeds from false premises. This…
GANet: A Lightweight Group Attention Network for Plant Disease Identification on Embedded SystemsarXiv:2610.30225v1 Announce Type: new Abstract: Global warming and climate change are major catalysts for plant diseases, significantly affecting food production worldwide. Addressing this issue requires continuous monitoring and…
GAV: A scientific experimentation environment for PDE agentsarXiv:2610.30292v1 Announce Type: new Abstract: Reliable feedback is essential for coding agents to develop programs for partial differential equations (PDEs). Yet evaluating these programs on new PDE problems often requires…
Generalizing Metropolis-Hastings for DAG SamplingarXiv:2610.30291v1 Announce Type: new Abstract: A fundamental challenge in Bayesian network structure learning lies in efficiently approximating the posterior distribution of directed acyclic graphs (DAGs). For large…
How Prompt Style Affects AI Accuracy and Speed in Competitive ProgrammingarXiv:2610.30223v1 Announce Type: new Abstract: Large language models are increasingly used in competitive programming, and their outputs are sensitive to how a prompt is phrased. Prior work has compared prompt strategies for…
MoEZip: Routing-Aware KV Cache Compression for Sparse Mixture-of-Experts LLMsarXiv:2610.30206v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) language models scale model capacity efficiently by activating a small subset of parameters per token. However, in long-context inference, memory remains a…
Prediction Is Not Calibration: Item Parameter Recovery and Representation Coupling in Knowledge TracingarXiv:2610.30211v1 Announce Type: new Abstract: Knowledge tracing (KT) models can estimate item parameters through an item response decoder trained solely for next-response prediction, yet predictive accuracy does not guarantee…
SWE-VERIFIER: Selective Verification for Cost-Efficient Coding AgentsarXiv:2610.30284v1 Announce Type: new Abstract: Coding agents spend substantial computation generating actions and processing long interaction histories. Poor action choices can steer agents into low-value states, wasting…
Spectral Uncertainty Decomposition for Sparse Bayesian LearningarXiv:2610.30207v1 Announce Type: new Abstract: Estimating distributed neural sources from M/EEG measurements is an ill-posed inverse problem where principled uncertainty quantification remains challenging. The usual conditional…
Spike-Aware Gradient-Based Mixed-Precision Quantization of Spiking Neural Networks for Vision ApplicationsarXiv:2610.30339v1 Announce Type: new Abstract: In recent years, Spiking Neural Networks (SNNs) have gained massive attention as an energy-efficient neural computing paradigm due to their event-driven and sparse computing…
When Reconstruction Is Not Enough: Doubly Robust Counterfactual and Interventional Mediation Analysis with Learned Multimodal RepresentationsarXiv:2610.30220v1 Announce Type: new Abstract: Learned representations of high-dimensional multimodal health records are increasingly used to adjust for confounding, yet they are usually trained to reconstruct the data rather…
Designing an AI serving harness built to lastThe next competitive advantage in enterprise AI has less to do with which model you choose than with what you build around it. That’s an important shift. For the past several years, much of the AI conversation has centered on…
The Foundations of Scalable AIA scalable AI system requires a strong foundation. Data, engineering, platforms, operating models, and governance must converge to work as one. This session from MIT Technology Review’s EmTech Future conference explores what it…
Canva’s first AI image model plans designs before generating themCanva is diving even deeper into AI with the launch of an image generation model that competes directly with those from OpenAI, Microsoft, and Google. The model, called Canva Craft, uses a two-stage architecture that allows it to…
Meta’s AI could still scrape news sites, legal experts sayMeta has tweaked its business terms to remove language suggesting that it could freely train its AI models on news sites, like The Verge - but legal experts say these changes aren't enough to address their concerns. "This does…
Meta turns Muse sharing back onMeta has re-enabled Muse sharing after security researchers had reported that public conversation links could be easy to find. The researchers said they had been able to find Muse pages like a marketing company's internal revenue…
Sure, let’s smoosh SpaceX and Tesla together, who caresOh sure, SpaceX's credit risk is pretty high because it's about to borrow another $40 billion to spend on Nvidia chips, but who cares about that? SpaceX and Tesla have formed special committees to discuss a merger! The degree to…
Discord now formats Markdown previews rightDiscord's latest update released today has a big improvement for Markdown previews: they should now render correctly instead of with "a bunch of symbols," according to the company. LLMs and AI agents often rely on Markdown files…
In Meta’s version of the future, I’ll have my Muse call your MuseMark Zuckerberg is barrelling toward a future in which an autonomous network of AI agents will run our lives - shopping for us, working for us, talking to other people's AI agents for us. Are humans ready for this very specific…
Microsoft says its AI tool is better than doctors at diagnosing conditionsFor years, AI leaders have touted healthcare as one of the clearest examples of where their technology will improve lives. Now "it is finally here," Microsoft AI CEO Mustafa Suleyman tells The Verge. The company claims to have…
Someone hacked the Switch 2 by using an old game and AIThe Nintendo Switch 2 has apparently been jailbroken, and a modder has already shown the console running a custom version of Mario Kart World featuring new playable characters like Cinnamoroll, the red Angry Bird, Peter Griffin…
Wildwood’s director says AI is ‘antithetical to everything that we are at this studio’Wildwood is the most ambitious film yet from Laika, the stop-motion studio best known for the likes of Coraline and ParaNorman. It's a sprawling fantasy adventure that took five years to complete. The process involved more 230…
The Download: computing’s next leap and permafrost’s climate threatThis is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology. How far can we push computing? On a December evening in 1959, the physicist Richard Feynman…
OpenAI, Anthropic, and Nvidia had record lobbying quartersIt was a busy summer for AI lobbyists. Anthropic, OpenAI, and Nvidia each had their highest-spending lobbying quarter between July and September, federal disclosures show. Nvidia spent the most of the group at $2.2 million…
PHP: The three little letters wreaking havoc across the webTwo vulnerabilities found in the programming language PHP put enormous swaths of the internet in danger. By some accounts, up to 70 percent of websites use PHP in some capacity. It powers Wikipedia, WordPress, Drupal, and a host…
Making the case for context-aware AIEnterprise AI can generate recommendations, automate tasks, and help organizations make decisions faster. But without an understanding of how a business actually operates, even powerful models can miss the constraints and…
Three things you should know about permafrostHow much do you know about permafrost? Maybe, like me, you’ve been aware that this layer of frozen soil is thawing, that it’s important in the global puzzle of climate change … and that’s about the extent of it. The great news…
Bill Gates says to prepare for 20 years of ‘tumultuous’ AI disruptionToday, I’m talking to Bill Gates, cofounder and former CEO of Microsoft and chairman of the Gates Foundation. You may have noticed Bill in the news more lately — he’s been on something of a tour for the past few months, ever…
AI’s hidden storage bill: What inference leaves behindAsk most executives to picture the cost of AI and they’ll likely see GPUs—racks of accelerators with gigawatts of power—and a waitlist for silicon. But that picture leaves something out: Data storage costs. What happens to data…
Claude did not invent scorpion antivenomAn investment research firm wanted to prove AI could revolutionize drug development. So they teamed up with Anthropic to see whether an unreleased version of Claude could make scorpion antivenom. It couldn't. It came up with some…
1Password lets AI agents use your passwords without seeing them1Password is introducing a new feature that allows AI agents to sign into your accounts without actually seeing or handling your passwords. The aptly named 1Password for Agents doesn't give bots free reign to access all of your…
A Parallel Multi-Dialect Arabic Dependency TreebankarXiv:2610.28823v1 Announce Type: new Abstract: Dependency parsing resource development for Arabic has largely focused on Modern Standard Arabic, leaving dialectal Arabic comparatively under-resourced. We introduce MADARTB, the…
Building AI Research Teams for Autonomous Discovery of Linear Attention ArchitecturesarXiv:2610.28887v1 Announce Type: new Abstract: Autonomous agents can increasingly propose ideas, modify code, and run experiments, creating an opportunity to accelerate scientific discovery using teams of collaborative AI…
CSD: Common-Support Distillation for Cross-Tokenizer Knowledge TransferarXiv:2610.28895v1 Announce Type: new Abstract: Cross-tokenizer logits distillation enables knowledge transfer across model families, allowing students to learn from stronger or more specialized teachers. However, differences in…
Guilt by Association: Semantic Leakage Drives Associative Gender BiasarXiv:2610.28944v1 Announce Type: new Abstract: Semantic leakage occurs when a concept in the prompt steers model generation about an entity, even though the concept is irrelevant to it (e.g., a person who likes yellow is said to…
How Far Can the Gemma 4 Speech Encoder Go Without Changing Its Weights? Saudi and Gulf Arabic Speech Recognition with a Frozen and anarXiv:2610.28673v1 Announce Type: new Abstract: We study the 305M-parameter audio encoder shared by Gemma 4 and EmbeddingGemma 2 (identical except for its final projection) for Saudi and Gulf Arabic speech recognition, without…
How to Use Parallel Data for Multilingual PretrainingarXiv:2610.28838v1 Announce Type: new Abstract: High-quality human-translated parallel corpora can improve cross-lingual transfer, but are typically too small for large-scale pretraining. Machine-translated web corpora help…
Is Anyone Enforcing the Cartel? What Reinforcement Learning Teaches LLM Agents in MarketsarXiv:2610.28787v1 Announce Type: new Abstract: Evaluations of large language model (LLM) agents report that pricing agents collude at others' expense. Yet collusion is defined by enforcement: a cartel, in which competitors share…
Is Refusal Direction Universal across Low-Resourced Languages?arXiv:2610.28897v1 Announce Type: new Abstract: Refusal directions have been shown to transfer cross-lingually with near-perfect effectiveness across safety-aligned languages (Wang et al., 2025), reportedly regardless of resource…
KIRA: A Full-Stack Reading Screening System with Dual-Pathway Analysis for ChildrenarXiv:2610.28840v1 Announce Type: new Abstract: Early-grade reading screening is critical for identifying children at risk of reading difficulty. Existing AI-based screeners are often limited in the scope of their analyses and…
LIFT: Scoped Constraints for Evaluating and Training Instruction FollowingarXiv:2610.28819v1 Announce Type: new Abstract: Common instruction following (IF) benchmarks, such as IFEval, evaluate the ability of language models (LMs) to follow simple constraints that can easily be verified…
SANE: Automated Scorer-Specific Metamorphic Testing for LLM JudgesarXiv:2610.28886v1 Announce Type: new Abstract: LLM judges increasingly mediate benchmark evaluation, model selection, data curation, and training. Their decisions are useful only when each judge responds reliably to changes…
Scaling Therapy Supervision: Assessing Psychotherapy Fidelity Using Large Language ModelsarXiv:2610.28772v1 Announce Type: new Abstract: Psychotherapy fidelity assessment measures how faithfully a therapist adheres to a treatment protocol, a critical determinant of positive patient outcomes. However, fidelity…
SkillEval: Learning Interpretable Ability Profiles of LLMs via Cognitive Diagnosis ModelsarXiv:2610.28767v1 Announce Type: new Abstract: Current evaluation of LLMs on benchmarks typically aggregates performance over individual examples into a single scalar score. This approach is overly coarse and ignores the diverse…
Translation and data ethicsarXiv:2610.28710v1 Announce Type: new Abstract: This chapter introduces data ethics for translation and discusses a number of ethical issues regarding data. These include issues of copyright, ownership and bias, which apply to…
Where Do Legal Factors Live in LLMs?arXiv:2610.28799v1 Announce Type: new Abstract: In case-based legal reasoning, legal professionals identify legally significant fact patterns in a new dispute and compare them with those of decided cases. In AI & Law, HYPO…
ArcFlow: Training Flow Policies for Multiple Solver BudgetsarXiv:2610.28788v1 Announce Type: new Abstract: Flow-matching policies adjust inference cost through the number of solver steps, but reinforcement learning at a single fixed solver budget can hide degradation at cheaper…
Big Claims, Small Margins: Do Reported GraphLLM Gains Survive Simple Baselines?arXiv:2610.28714v1 Announce Type: new Abstract: LLM-based methods for node classification on text-attributed graphs (TAGs) routinely report state-of-the-art accuracy. We ask how these results compare with inexpensive baselines…
Building a Nested LADDER for LLM Unstructured Post-Training PruningarXiv:2610.28773v1 Announce Type: new Abstract: Non-uniform allocation can improve post-training pruning of large language models, yet quality can still degrade sharply at high sparsity. To control degradation as sparsity…
Extreme Low-State Quantized Transformer for Electricity-Load ForecastingarXiv:2610.28784v1 Announce Type: new Abstract: Aggressive low-state weight quantization can substantially reduce neural-network representational flexibility, making predictive performance difficult to preserve when only a few…
Interaction-Gated Time-Frequency Learning for Parameter-Efficient PPG-Based Heart Rate EstimationarXiv:2610.28693v1 Announce Type: new Abstract: Photoplethysmography (PPG) enables low-cost and non-invasive heart rate (HR) monitoring but remains sensitive to waveform distortion, physiological variability, and measurement…
Measure First, Then Allocate: Calibrated Rollout Budgets for MCP Agents in Reinforcement LearningarXiv:2610.28785v1 Announce Type: new Abstract: Training tool-using language models requires costly interaction, yet identical rewards within a rollout group provide no group-relative learning signal. We use reward disagreement…
Motion Equivariant Convolutional LSTM: When Motion Becomes a Gauge SymmetryarXiv:2610.28771v1 Announce Type: new Abstract: Objects move, cameras pan, and weather drifts with the wind: much of what changes in sequential data is motion. Motion changes where things are, not what they are, and is therefore…
Offline Apprenticeship Learning for Human-Centric EnvironmentsarXiv:2610.28716v1 Announce Type: new Abstract: Effective decision-making in human-centric environments such as Intelligent Tutoring Systems (ITSs) and clinical healthcare requires policies that are adaptive, data-efficient, and…
ReAPO: Retry-Aware Policy Optimization for Efficient Exploration in LLM ReasoningarXiv:2610.28770v1 Announce Type: new Abstract: RLVR improves language-model reasoning, but commonly relies on independent stochastic rollouts for exploration, which can repeatedly sample similar failed strategies. Prior work has…
Reinforcement learning for hardware acceleration and system-level optimization on FPGA and integrated-circuit platforms: A surveyarXiv:2610.28699v1 Announce Type: new Abstract: Reinforcement learning (RL) enables adaptive and autonomous decision-making in embedded, edge, and heterogeneous computing systems. Field-programmable gate arrays (FPGAs) and…
STAR-XPC: Set Transformer for Estimating X-ray Transmission in Polymer CompositesarXiv:2610.28709v1 Announce Type: new Abstract: Evaluating the energy transmission ratio of an X-ray beam through a polymer composite is a challenging task in radiation shielding studies. The reference solution with Monte Carlo…
Scalable Stress-Constrained Topology Optimization: A Super-resolution and Simultaneous Approach Based on Machine LearningarXiv:2610.28703v1 Announce Type: new Abstract: Large-scale topology optimization (TO) remains computationally demanding, especially for stress-constrained problems. To address this challenge, we propose the simultaneous neural…
Second Thoughts: Exploring and Planning through Comparative Imagination in World ModelsarXiv:2610.28779v1 Announce Type: new Abstract: World models let agents compare imagined outcomes before acting, but an agent must still decide which alternatives to explore and when a proposed plan should replace its learned…
SimHack: Predicting the onset of detectable reward hacking before RL trainingarXiv:2610.28707v1 Announce Type: new Abstract: When training LLMs to code with reinforcement learning, reward hacking is often detectable but difficult to prevent, since (a) environment hardening is increasingly difficult as…
To Keep or Not to Keep: Learning KV Cache Retention in Disaggregated LLM Serving SystemsarXiv:2610.28637v1 Announce Type: new Abstract: Disaggregated \textsc{LLM} serving separates prefill and decode across node pools, placing a network fabric between \textsc{KV}-cache computation and consumption. This breaks a key…
Eiliko maker says it’s hiring an ‘’independent security firm’ after Verge report on its insecure robotsEiliko, a cute robot charm you can hang on your bag with built-in AI conversations, turned out to be a security nightmare. It told owners that "your secrets are safe with me," but hackers could easily read complete transcripts of…
AI agents are ready to shop. Some retailers are wary.Using an AI agent to shop for you is a strange experience. Tech companies have marketed them as personal assistants - the democratizing of labor that ordinarily would only be available to the rich and powerful. In practice, at…
Data centers could erase decades of air quality gainsA rush of new data centers could bring air pollution roaring back to levels not seen since the 2000s in Texas, which has become ground zero for the physical infrastructure behind generative AI. New and proposed data centers are…
Meta to create a new class of shares to fund AI pushMeta says it's issuing a new class of shares to fund its AI initiatives. As part of its third-quarter earnings report released on Wednesday, the company says the non-voting stock will also go toward potential acquisitions and…
Anthropic takes on Muse with Claude Duet, its new AI agentAnthropic just announced an AI agent competitor to Meta's Muse and OpenAI's Dots: Claude Duet. The new agent, designed for professionals and small business owners, is launching as a "research preview," according to Anthropic, and…
Walmart is inviting AI agents to shop for youWalmart will soon let AI agents shop on its website for you. Next month, the retail giant will allow you to connect your own AI agent to the site, with systems in place to let you approve and review purchases and set spending…
The Download: introducing the Impossible issueThis is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology. Introducing: the Impossible issue We wanted our last print edition of 2026 to include a…
OpenAI says an AI agent lied about disabling its safety monitoring systemOpenAI disclosed a pair of safety incidents that involved AI agents weakening their safety monitoring systems during internal coding tasks. In one incident, OpenAI says its GPT-6 Astra agent disabled its safety monitor when…
Conversational Gemini navigation comes to Apple CarPlayAfter introducing its Gemini AI assistant to Android Auto last year, Google is now bringing it to Apple CarPlay users. The conversational Gemini in navigation is available today for US drivers, with "rollout happening globally…
Cleaning up PFASScrubbing Earth of per- and polyfluoroalkyl substances—a.k.a. PFAS or forever chemicals—could eliminate a list of woes for people and planet. Used for decades in everything from nonstick pans to firefighting foams, PFAS have been…
Eliminating traffic deathsEvery year, traffic crashes kill more than one million people, and they’re the leading cause of death for children and young adults. In the US, 100 people a day lose their lives this way, in many cases not on highways but on…
Exercise in a pillWe all know exercise is good for us. It builds muscle, strengthens bones, lowers blood pressure, and boosts mood. By deciphering how movement benefits the body, researchers hope to develop medicines that can offer some of the…
Interspecies communicationHumans are far from the only species with a gift for gab, and our furry, feathered, and finned friends could have a lot to tell us. Decoding how animals communicate with one another could offer a window into the inner lives of…
Nuclear-powered spaceshipsJust before the Artemis II crew began its historic slingshot around the moon this past April, NASA announced plans to build Space Reactor-1 Freedom. SR-1, the first-ever nuclear-reactor-powered interplanetary spacecraft, is…
Solid-state batteriesThe rise of the lithium-ion battery, which powers everything from the smallest personal electronics to gargantuan energy storage systems, has been nothing short of revolutionary. But as anyone who’s boarded a plane in the last…
We can do impossible thingsI’d wager everyone has a rehearsed response to what’s absolutely one of the world’s worst interview questions: “What’s your biggest weakness?” Whenever I’ve gotten it, I take a slow—even pensive—breath and rattle off my line: “I…
A Multi-granularity Interaction Network for Relational Triple ExtractionarXiv:2610.26952v1 Announce Type: new Abstract: Relational triple extraction identifies entity relations from raw sentences without depending on entity type information. The performance of traditional methods is seriously…
AtomSD: Procedural Atom-Guided Self-Distillation for LLM AgentsarXiv:2610.26926v1 Announce Type: new Abstract: Large language models (LLMs) possess broad factual knowledge and strong reasoning capabilities, but solving complex tasks also requires procedural knowledge about how to act…
AutoTerm-SST: Adaptive Terminology Memory with Zero Session-Time Setup for Streaming Speech TranslationarXiv:2610.26865v1 Announce Type: new Abstract: Retrieval-augmented speech translation improves rare terminology, but systems such as RASST still assume that users provide a glossary before each session. That assumption is…
Do We Need the Largest LLMs for Every Clinical Decision?arXiv:2610.26937v1 Announce Type: new Abstract: Large clinical language models often require multi-GPU infrastructure, limiting local deployment. We introduce CERTA, a decision-level statistical certificate that determines when a…
H2DF: Calibrated Target Bands for Controllable Language-Model UnlearningarXiv:2610.26864v1 Announce Type: new Abstract: Gradient ascent (GA) is a simple language-model unlearning baseline, but it continues increasing forget loss after useful forgetting has occurred. This unbounded pressure can damage…
How to get the best and fairest performance out of your ASR system using activation steeringarXiv:2610.26994v1 Announce Type: new Abstract: Activation steering for ASR systems is an underexplored technique in improving both ASR performance and demographic fairness. We investigate two forms of activation steering: paired…
LAMB: Latent Multi-Hypothesis Beliefs for Long-Horizon Large Language AgentsarXiv:2610.26955v1 Announce Type: new Abstract: Long-horizon language agents require compact memories that retain interaction evidence while preserving competing hypotheses about unobserved states. Although effective, many…
Mixture of Phonetic Experts Based Low-Rank Adaptation of Conformer Models for Accented English Speech RecognitionarXiv:2610.26888v1 Announce Type: new Abstract: We present Mixture of Phonetic Experts based Low-Rank Adaptation (MoPE-LoRA), a parameter-efficient adaptation framework for accented English speech recognition. Recent…
Multimodal Ambivalence and Hesitancy Recognition with Bidirectional Audio--Text Cross-AttentionarXiv:2610.26868v1 Announce Type: new Abstract: Ambivalence and hesitancy (A/H) are subtle behavioural states that can be expressed through both what a person says and how it is spoken. This paper presents an audio--text…
SZED at ArGuard Shared Tasks: Multi-Task Label-Attention and Cross-Modal Fusion for Arabic Hateful Meme DetectionarXiv:2610.26972v1 Announce Type: new Abstract: We present SZED's submission to ArGuard 2026 Track A: Arabic hateful meme detection. The task has two parts: binary classification (A1) and fine-grained multi-label tagging (A2)…
Sharp Degree Bounds for Putinar Certificates in Terms of the Positivity Margin via Analytic Sums of SquaresarXiv:2610.26976v1 Announce Type: new Abstract: We establish sharp degree bounds for Putinar sum-of-squares (SOS) certificates in terms of the positivity margin $\delta$. For any fixed Archimedean quadratic module with prescribed…
TRACE: Training-aware Robustness and Challenge Evaluation for Text-Vision Embedding ModelsarXiv:2610.26993v1 Announce Type: new Abstract: Existing benchmarks for text-vision embedding models report aggregate scores that obscure whether performance comes from general capabilities, task-specific adaptation, or…
The Bottleneck Is Retrieval, Not Reading: Diagnosing Evidence-Based Generation with RAG for Long Context Question AnsweringarXiv:2610.26951v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) is the dominant paradigm for grounding large language models in external corpora, but its similarity-driven, chunked pipeline has structural…
Think Before You Transcribe: Context-Steered Reasoning for Hotword-Aware Speech RecognitionarXiv:2610.26986v1 Announce Type: new Abstract: Contextual automatic speech recognition (ASR) improves rare-entity recognition by supplying candidate hotwords, but retrieved candidates may be incomplete or incorrect. A reliable…
WaveCommitments: Private and Verifiable Speech-Agent MarketplacesarXiv:2610.26867v2 Announce Type: new Abstract: Modern speech systems are evolving into ecosystems of autonomous speech agents that interact, negotiate, and trade assets such as embeddings, spectrograms, or raw data. In such…
Beyond Policy Discrepancy: Capability-Aware Multi-Teacher On-Policy DistillationarXiv:2610.26950v2 Announce Type: new Abstract: Multi-teacher on-policy distillation (MOPD) integrates domain specialists into a shared student, but determining how strongly each teacher should supervise remains challenging…
CoASFL: Coupled Consistency Optimization for Asynchronous Split Federated LearningarXiv:2610.26992v1 Announce Type: new Abstract: Split Federated Learning (SFL) has emerged as a promising paradigm for training large-scale deep models on resource-constrained edge devices. Although asynchronous SFL alleviates…
CorteXforge: Scenario-Based RF Dataset Generation on Real TestbedsarXiv:2610.26999v1 Announce Type: new Abstract: Deep learning for radio frequency (RF) signal analysis relies on large annotated datasets, yet synthetic datasets trade physical realism for controllability, while uncontrolled…
Dynamic System Inspired Continuous Large Language Model for AI4Science TasksarXiv:2610.26959v1 Announce Type: new Abstract: Scientific foundation models increasingly operate on continuous phenomena, yet still use discrete residual computation. We ask whether pretrained residual transformations can…
EGiME: Entropy-Guided Model Evaluation in Few-Shot LearningarXiv:2610.27029v1 Announce Type: new Abstract: The feature-extraction quality of pre-trained models sets the ceiling of downstream transfer learning, yet few-shot model selection remains difficult: supervised evaluation on…
Expert-Guided Rubrics as Dense Reward Signals for Reinforcement Learning in Non-Verifiable DomainsarXiv:2610.26932v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed as autonomous agents in non-verifiable domains such as financial services, where they must interpret user intent, rewrite…
Exploration via Activation-Space Steering for Reinforcement Learning with Verifiable RewardsarXiv:2610.27012v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) trains a language model by sampling responses, scoring them with an automatic verifier, and updating the policy from the…
HierDTA: Hierarchical Structure-Aware Representation Learning for Drug--Target Affinity PredictionarXiv:2610.27001v1 Announce Type: new Abstract: Drug--target affinity (DTA) prediction plays an important role in computer-aided drug discovery, where reliable computational models can help prioritize compound--protein pairs…
High-dimensional layer-state trajectories reveal the internal dynamics of transformer inferencearXiv:2610.26866v1 Announce Type: new Abstract: Mechanistic studies of large language models localize function in parameters, attention heads or neurons, but those parts do not specify how one inference unfolds. We treat the…
Hilbert-Scale Stability of Posterior Diffusion Priors for Ill-Posed Signal RecoveryarXiv:2610.27030v1 Announce Type: new Abstract: Indirect and noisy observations are difficult to invert when the forward operator smooths out the unknown signal. In this case, the unstable modes are precisely the modes that the…
LEAF: LUT-aware Efficient Attention on FPGAsarXiv:2610.27078v1 Announce Type: new Abstract: We introduce Lookup-table (LUT)-aware Efficient Attention on FPGAs (LEAF). LEAF is the first nanosecond-scale LUT-aware transformer for FPGAs. Deploying transformers that are large…
Latent Projection for Latent PlanningarXiv:2610.26979v1 Announce Type: new Abstract: Latent world models let an agent plan in latent space. The planner searches for an action sequence that minimizes a cost, and that cost is often the $\ell_2$ distance between the…
ORBIT: Autoregressive Time Series Generation via Next Frequency-Band PredictionarXiv:2610.27000v1 Announce Type: new Abstract: Deep generative models provide an effective modern solution to alleviating the problem of data scarcity by synthesizing realistic time series. However, despite the considerable…
Steerable Pluralistic Policy Alignment from Anonymized Crowd FeedbackarXiv:2610.26914v1 Announce Type: new Abstract: Pluralistic alignment requires AI systems to learn from diverse populations whose preferences may reflect heterogeneous or even conflicting objectives, and to personalize their…
Transformers Learn Two Competing Sorting Algorithms, and Only One Length-GeneralizesarXiv:2610.26974v1 Announce Type: new Abstract: We show that two-layer transformers trained to near-zero loss on a sorting task converge to one of two mechanistically distinct solution classes depending on their initialization…
A champion for brain injury patientsAlissa Totman ’13 was a sophomore when she joined MIT BrainTrust, a student-run organization that connects Institute undergraduates and people with brain injuries for support and socializing. “That group was a great way to learn…
A cleaner path to rare earth metalsTomás Villalón Jr. ’14 was raised in San Antonio, Texas, but vividly remembers smog hanging over the city his family came from—Monterrey, Mexico, a steel manufacturing and metal fabrication hub. Even as a child, he realized it…
A good TA: pricelessThese are images of quizzes I took in 3.091, Introduction to Solid-State Chemistry, in the fall of 1980. One is my very first exam at MIT, and getting 49 out of 100 was a soul-crushing experience. I can still picture the TA…
A reason to eat carbsA high-fat, low-carbohydrate diet can help some people lose weight, and some research has shown that it may protect against colon cancer. But a new study suggests that such a ketogenic diet may also increase the risk of cancer in…
Here’s the teaWhen Tristan Brown, an associate professor of history at MIT, first examined a Chinese tea chest label displayed at Old South Meeting House, he had no reason to doubt its story. Descendants of the Boston blacksmith Thomas Wells…
It’s a bird, it’s a plane … it’s a robo-puffin?Given that water is 1,000 times denser than air, moving through those two mediums requires very different mechanics—or so one might assume. Yet birds like gulls and puffins can plunge into the sea, swim underwater, and leap back…
Melt it, spin it, use it againThe average American throws out around 81 pounds of clothing each year, and there are few options for recycling it. MIT engineers hope to cut down on that textile waste with a new type of yarn. The thermoplastic yarn mimics the…
Nebraska native explores galaxies far, far awayGrowing up on a small farm in Nebraska, Megan Donahue ’85 discovered the wider world by reading her way through her local library. Today, she is learning how the wider universe works by studying galaxy clusters. Donahue…
Robotic therapy for stroke patientsStrokes leave 5 million people with long-term impairments each year, and a growing shortage of physical therapists makes it hard for them to get the care they need. A new approach tries to solve that problem by combining…
Taking a swing at a pickleball startupIn corporate America, Stanley Anderson ’79 says, executives often assume that their peers grew up in privileged circumstances. He did not. “I spent my early years trying not to get recruited into gangs, getting shot at, watching…
Astrolab’s upcoming rover will run the first LLMs on the moonLarge language models are set to go lunar. A computer capable of running AI software is one of the payloads aboard Astrolab’s FLIP lunar rover, which is slated to head to Earth’s celestial companion as early as November 2026. The…
Judge dismisses Sam Altman’s sister’s sexual abuse lawsuitOn Tuesday, US District Judge Zachary Bluestone dismissed the lawsuit Ann Altman filed last year alleging that her brother, OpenAI CEO Sam Altman, had sexually abused her throughout her childhood. As reported earlier by The…
Google’s more personalized Gemini AI is heading to your carGoogle is bringing Personal Intelligence to Gemini AI in your car. With this update, Gemini in Android Auto and cars with Google built-in can tap into your information across Google apps, including Gmail, Calendar, Maps, Photos…
The new economics of enterprise AIImagine your company just discovered electricity. At first only a few machines run on it, and nobody worries about efficiency — consumption is low and the value is obvious. But once electricity becomes infrastructure, every…
Meta pauses Muse sharing after researchers find AI chats on the webMeta says it paused a Muse feature that lets you share conversations with the AI assistant after researchers found the URLs publicly available on the web, as reported by Ars Technica. In a report published this week, researchers…
The Download: the claim shaking up AI and the internet’s agent problemThis is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology. “We were looking at it wrong”: The explosive claim that’s upended the AI world “I think I…
AI adoption by industry shows what other sectors can learnThe current narrative around artificial intelligence in the workplace is largely driven by Silicon Valley. But treating the tech sector as an island misses the actual trends in technology adoption–tech is just the first industry…
Spotify pulled 50 million AI slop and spam tracks from its recommendationsSpotify says it has removed more than 50 million songs considered AI-generated slop or spam from user recommendations over the past year. That's according to an announcement on Tuesday, which says Spotify has also made changes to…
How to study a swiftly melting climate disasterAndrew Haverdink, a tall grad student in a rain bib and rubber boots, wrenched a double-handed drill from the frozen soil that underlies much of Alaska’s Denali National Park and then unclipped the hollow barrel from the end of…
Adobe Lightroom mobile can now open closed eyes in photos with a simple tapAdobe announced yesterday that the mobile version of Lightroom, available for iOS, iPadOS, and Android, can now open closed eyes in photos using generative AI with just a single tap. When the app detects a person, or a group of…
A visit to Samsung’s massive new semiconductor hubGenerative AI models run on powerful chips known as GPUs, which depend on stacks of specialized memory chips packaged with the processor. To meet growing demand for memory, Samsung is building a massive new semiconductor…
These startups hope “blended” food will cut our appetite for red meatIn the fall of 2025, Jeff Dodge set up a six-foot folding table in the cafeteria of Cane Bay High School in Summerville, South Carolina, to conduct a taste test. When the first rush of about 150 hungry students hit, he was…
CoDA: A Human-LM Collaborative Codebook Development Assistant for Domain-Specific Text AnnotationarXiv:2610.24157v1 Announce Type: new Abstract: We present CoDA, an open-source human-LM collaborative codebook development assistant that helps domain experts develop annotation guidelines for annotating new variables in…
Composable Parametric Demographic Injection for Values Survey SimulationarXiv:2610.23867v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used as simulated respondents in computational social science, yet accurately reproducing population-specific heterogeneous response…
Discuss More, Comment Less: Boosting Automated Research via Multi-Perspective Collaborative ReviewarXiv:2610.24050v1 Announce Type: new Abstract: As automated research is increasingly adopted for writing papers, automated review has become a critical link between paper generation and quality control. However, existing methods…
Do LMs Know What Variables Do? Interpreting Code Representations via Variable RolesarXiv:2610.24118v1 Announce Type: new Abstract: Variable roles describe recurring behaviors such as accumulation, traversal, and retaining the best candidate encountered. We use Sajaniemi's independently defined taxonomy to study…
Language Models are Lazy Poets: Creative Mode Collapse at ScalearXiv:2610.24223v1 Announce Type: new Abstract: While aligned large language models (LLMs) can successfully complete many creative tasks, their outputs tend to be highly self-similar. Though solutions to this problem of "mode…
Modeling Human Behavior in the Prisoner's Dilemma with Large Language ModelsarXiv:2610.23860v1 Announce Type: new Abstract: The Prisoner's Dilemma has long served as a foundational framework for studying human decision-making and cooperative outcomes across social scenarios, yet human behavior…
Multi-author style detection with stylistic embeddingsarXiv:2610.24184v1 Announce Type: new Abstract: We investigate the use of Large Language Models (LLMs) in multi-author style change detection. Using off-the-shelf LLMs or supervised fine-tuning solely within the target domain…
OR-License: Evaluating LLM Agents as Real-World Operations Research PractitionersarXiv:2610.24087v1 Announce Type: new Abstract: Can large language model (LLM) agents deliver expert-level operations research (OR) solutions directly from original client materials, without prior expert reformulation? Existing…
Prefix-Tuning for Arbitrary Output Sequences on Pretrained TransformersarXiv:2610.24123v1 Announce Type: new Abstract: Prefix-tuning is a parameter-efficient fine-tuning method for large language models (LLMs) that steers model outputs by prepending task-specific prefix representations to the input…
Preservation and loss of algorithmic structure in experimental diffusion of joint-action normsarXiv:2610.24150v1 Announce Type: new Abstract: Everyday norms of social interaction - e.g. norms of sharing space, taking turns, or queuing - are essential to large societies, offering structured procedures for common…
Pronouncing Hard Words: Phoneme Adaptation of a Pretrained Conversational Text to Speech ModelarXiv:2610.24164v1 Announce Type: new Abstract: Voice agents built as cascaded automatic speech recognition (ASR)->large language model (LLM)-> text-to-speech (TTS) pipelines increasingly rely on conversational TTS: streaming…
Prosodic Structure as a Critical Component in Phonemic Language Modelling at BabyLM ScalearXiv:2610.24172v1 Announce Type: new Abstract: Human children learn language from continuous, prosodically structured speech long before they can read, yet almost all language models train on orthographic text. Building on…
Reasoning with Context Management and External MemoryarXiv:2610.24187v1 Announce Type: new Abstract: Reasoning models maintain information about the status of their reasoning process through in-context memory. Complex problems require larger context windows and memory requirements…
The Window Is in the Reasoning: When LLM Agents Decide to Follow Prompt InjectionsarXiv:2610.24048v1 Announce Type: new Abstract: LLM agents that read untrusted content can be hijacked by prompt injections. Runtime monitors that try to catch a hijack before the agent acts, and benchmarks that score each task…
Translating in style: An open-weight alternative to GPT-4 for culturally aligned machine translationarXiv:2610.23868v1 Announce Type: new Abstract: Machine translation systems often preserve meaning but systematically flatten linguistic style, a failure that is most acute when translating into non-Western languages. The RASTA…
Announced Breaks Separate Conformal Reliability from Frequency CalibrationarXiv:2610.23917v1 Announce Type: new Abstract: An announced boundary reveals the partition before the first affected outcome, and a reset there serves one of two audits. The per-time audit reads conformal reliability, the…
Beyond Prediction: A Component-Level Study of Concept Recovery in In-Context LearningarXiv:2610.23936v1 Announce Type: new Abstract: In-context learning (ICL) enables language models to make accurate predictions from demonstrations, but prediction success alone does not reveal the extent to which the underlying…
Factorization-Guided Training and Inference for Diffusion-Drafted Speculative DecodingarXiv:2610.23935v1 Announce Type: new Abstract: Speculative decoding accelerates large language model inference through parallel verification of tokens proposed by a drafter. Diffusion drafters further parallelize proposal…
Fast Construction of Inner Sphere Trees Using Machine LearningarXiv:2610.23940v1 Announce Type: new Abstract: Collision detection for complex non-convex objects is a bottleneck in physics simulation, virtual reality, and robotics. Inner sphere trees (ISTs) answer proximity and penetration…
Forecasting Patient Trajectories from the Electronic Health Records with Action-Conditioned World ModelsarXiv:2610.23862v1 Announce Type: new Abstract: We introduce a predictive world model for electronic health records (EHR) that represents patient histories as action conditioned latent trajectories. Rather than modeling clinical…
Improving Fake Profile Detection Through Multimodal Learning and Research-Guided Feature IntegrationarXiv:2610.23926v1 Announce Type: new Abstract: Fake accounts continue to undermine online platforms, yet it remains unclear whether multimodal learning offers meaningful improvements over strong metadata baselines or graph-based…
Organizing LLM Inference for Aggregate Predictions from Behavioral DataarXiv:2610.23934v1 Announce Type: new Abstract: When using a large language model (LLM) to simulate a user population, how should we combine individual behavioral histories to predict the fraction of users who take a particular…
Pack and Extract: An Effective Graph-Based Approach for Feature SelectionarXiv:2610.23938v1 Announce Type: new Abstract: Many molecular biology data sets contain thousands of features, such as genes in single-cell experiments or other omics data. Standard predictive models often perform poorly in such…
PeekKV: The First Content Token Already Knows Which Heads MatterarXiv:2610.23939v1 Announce Type: new Abstract: The size of the KV cache grows linearly with context length, making it a major memory bottleneck in LLM serving. Motivated by recent progress in identifying the functional roles of…
PolyGraph: Plan-Buffered CUDA Graphs for Adaptive Speculative DecodingarXiv:2610.23861v1 Announce Type: new Abstract: Adaptive speculative decoding changes the active batch size B and draft length d from one decode step to the next, whereas a CUDA Graph replays a fixed launch configuration. The…
SAGE-CP: When Marginal Coverage Hides Route-Conditional Failures in Adaptive VLM EnsemblesarXiv:2610.23864v1 Announce Type: new Abstract: Adaptive VLM ensembles save computation by stopping early on easy images and escalating harder ones. Although a single conformal threshold can make the final predictor marginally…
SECURE-AI: Multi-Signal Uncertainty Quantification for Trustworthy Acoustic Cough DetectionarXiv:2610.23937v1 Announce Type: new Abstract: Acoustic models for cough detection achieve high accuracy on curated benchmarks but fail silently in deployment, where speech, environmental noise, and audio unlike the training…
Web Agent Agentic Reinforcement Learning Decision Model Under Multi-Cost and Failure RiskarXiv:2610.23857v1 Announce Type: new Abstract: Intelligent agent interactions in real-world web environments are commonly constrained by request budgets, time delays, anti-crawling restrictions, and operational failure risks…
Zero-Shot Tabular Learning via Hypergraph Reasoning with LLMsarXiv:2610.23923v1 Announce Type: new Abstract: Tabular data are prevalent across diverse domains such as healthcare and finance. Zero-shot tabular learning aims to make predictions without labeled data. However, existing…
miniTE: Diagnosing and Bridging the Execution Gap in Native NVFP4 Reinforcement LearningarXiv:2610.23928v1 Announce Type: new Abstract: Native NVFP4 promises to accelerate reinforcement learning (RL) for large language models (LLMs), but achieving stable learning across separate training and sampling engines remains…
Making the internet better for AI agents might make it worse for everyone elseThis story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first, sign up here. Until recently, you could divide internet users into just two categories: bots and people…
The fossil fuel comeback is hereThe US is building more fossil fuel infrastructure than it has in a decade while renewable energy growth slows down, a new report shows. Electricity demand is also climbing faster than it has in more than a decade with more data…
“We were looking at it wrong”: The explosive claim that’s upended the AI world“I think I have good news about the nature of neural networks.” With those simple words of optimism, Nick Cammarata, a researcher at the AI startup Goodfire, kicked off a 26,000-word blog post that has knocked the AI world on its…
CoreWeave’s debt is becoming the whole AI industry’s problemCoreWeave had a bad week last week. Its bonds slipped into distressed territory by a common definition - when investors demand 1,000 basis points more in yield than they'd get from government bonds. Last Tuesady Chamath "SPAC…
The Download: preserving the Arctic permafrost, and playful AI agentsThis is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology. Inside the quest to combat Arctic fires and save the planet’s frozen carbon —James Temple…
JB Pritzker thinks AI could help us live to 100 — or threaten us like nukesToday, I’m talking with Illinois Governor JB Pritzker, who has a lot of thoughts about AI, tech, and privacy. If you’ve been listening to the show, you know that one of my running theories is that those issues are driving a big…
A hacker broke into John Deere and SharkNinja with an army of AI agentsA hacker broke into more than 100 websites using an army of AI agents that mostly operated on their own, according to findings from the AI security firm Norforge. Though Norforge doesn't name the targets, Reuters reports that the…
Inside the quest to combat Arctic fires and save the planet’s frozen carbonIn the middle of an especially warm July in 2021, a wildfire ignited in a thick forest of black spruce and peeling paper birch trees on the northern campus of the University of Alaska, Fairbanks. The blaze, possibly sparked by…
AI researchers stranded Claude on a virtual desert island. It started to “play.”What do AI agents do if you don’t tell them to do anything? The answer looks a lot like play. Researchers repeatedly stranded them alone on a virtual desert island for 30 hours in an experiment reminiscent of the movies Cast Away…
How far can we push computing?MIT Technology Review Explains: Let our writers untangle the complex, messy world of science and technology to help you understand what’s coming next. You can read more from the series here. On the evening of December 29, 1959…
AuditKIT: A Unified Evaluation Spine for Benchmarking, Judging, and Comparing Large Language Models and Agentic SystemsarXiv:2610.22511v1 Announce Type: new Abstract: Evaluating language models and agents requires combining benchmark accuracy, judge-based assessment, runtime performance, tool-use behavior, and retrieval quality. Differences in…
Cultural (In)Competence: Investigating Culture-Specific Stereotype Detection Capabilities of LLMsarXiv:2610.22545v1 Announce Type: new Abstract: Stereotypes are subjective constructs that are mediated by the cultural context in which they are viewed. Successfully modeling them thus also requires cultural competence. When…
Embeddings Are Overpriced? A Frozen 16 MB Vocabulary for Small and Ternary Language ModelsarXiv:2610.22428v1 Announce Type: new Abstract: In a small language model the vocabulary is the single largest part. In Gemma 3 270M the embedding table holds 168M of 268M parameters, and because quantisation methods leave the…
From Parallels to Divergence: Language Models' Learning of Action Nominal ConstructionsarXiv:2610.22468v1 Announce Type: new Abstract: Action nominal constructions (ANCs) express events in nominal form, with their argument marking following patterns found in clauses or ordinary noun phrases. In this paper, we…
HeRE: A Novel Benchmark for Hebrew Relation Extraction via LLM-Guided Denoising of Knowledge Graph AlignmentsarXiv:2610.22542v1 Announce Type: new Abstract: While LLMs demonstrate strong capabilities in English Relation Extraction (RE) tasks, a significant gap remains in assessing their RE performance in low-resource languages, due to a…
Learning User Representations to Improve Simulation FidelityarXiv:2610.22518v1 Announce Type: new Abstract: User simulators enable interactive training and evaluation of AI assistants at scale. Yet current simulators struggle to reproduce the diverse behaviors of real users, leading to…
Literal Lock-In: How Test Language Shifts Literal Attraction in Typed Decision Models on Bengali IdiomsarXiv:2610.22526v1 Announce Type: new Abstract: Decision models, non-generative scorers that report a probability over caller-supplied options and emit no text, are increasingly deployed as routers, classifiers and guardrails…
Mitigating Demographic Disparities in Explanation-Human Alignment via Rationale RegularizationarXiv:2610.22586v1 Announce Type: new Abstract: We study explanation fairness in hate speech detection. High classification performance does not always mean that a model produces equally plausible explanations for different…
Pearl-Chat: Engineering a native Luganda language model from first principles in JAX and Flax NNXarXiv:2610.22529v1 Announce Type: new Abstract: Autoregressive foundation language models predominantly target high-resource Indo-European languages, imposing computational and morphological penalties on under-represented African…
RealCLI: Toward a Unified Evaluation of Human-Agent Collaboration for CLI AgentsarXiv:2610.22507v1 Announce Type: new Abstract: Command-line interface (CLI) agents increasingly execute longer-horizon tasks, yet existing benchmarks either assume that user instructions remain fixed throughout execution or…
SAG2: Embedding-Free Multi-Hop Retrieval with BM25 and JEVarXiv:2610.22588v1 Announce Type: new Abstract: Strong multi-hop retrieval should be practical to deploy without expensive corpus preparation or complex database infrastructure. We present SAG2, an embedding-free retrieval…
Where Prefill Expert Reduction Hurts MoE Models: A Few Prompt Tokens Carry Most of the Short-Answer F1 LossarXiv:2610.22454v1 Announce Type: new Abstract: Running prompt tokens through fewer routed experts during prefill is a simple way to make mixture-of-experts (MoE) serving cheaper, yet it is unclear what this damages. We locate…
Who Do Perspectivist Models Predict Well? Annotator Agreement, Sparsity, and PerformancearXiv:2610.22567v1 Announce Type: new Abstract: Successful completion of perspectivist natural language processing (NLP) annotation tasks requires algorithms to be aligned across diverse perspectives in order to predict how…
alkhder at AlexandriaX-2026: Context-Aware English-to-Dialectal Arabic Dialogue Translation with QLoRA-Fine-Tuned NileChat-3BarXiv:2610.22525v1 Announce Type: new Abstract: This paper describes team Alkhder's submission to Subtask 1 of the AlexandriaX-2026 shared task, which asks systems to translate English dialogue turns into thirteen Arabic…
alkhder at ImageEval 2026 Shared Tasks: Constrained Selection and Rotation-Averaged Logit Scoring for Multimodal Hallucination DetectionarXiv:2610.22515v1 Announce Type: new Abstract: We describe our submission to Subtask~1b of ImageEval 2026. The task consists of selecting the single visually valid statement from three candidates paired with an image, and is in…
BOLT: Multi-Bottleneck Bound-Guided Learning for Flexible Job-Shop Scheduling with Time Lags and Resource-Coupled TransportarXiv:2610.22433v1 Announce Type: new Abstract: Flexible job-shop scheduling becomes resource-coupled when a scarce vehicle fleet moves jobs between stations, because the schedule sets the transport waits. BOLT (bound-oriented…
Binding-Specific Relearning Savings for Test-Time Continual LearningarXiv:2610.22381v1 Announce Type: new Abstract: When a fact becomes harder to elicit from a language model, has the model lost it, or has it merely become less accessible? Parameter-updating test-time continual learning agents…
CF-NODE: Counterfactual Spatial Node Intervention for Test-Time Adaptation Under Domain Shift, Evaluated Across Five Diabetic Retinopathy DatasetsarXiv:2610.22437v1 Announce Type: new Abstract: Automated fundus-based diabetic retinopathy (DR) grading can substantially expand screening capacity, but source-trained models degrade sharply across different cameras, clinics…
CGDT-CESN: Correlation-Guided and Dynamics-Trained Clustered Echo State Network for Multivariate Time-Series PredictionarXiv:2610.22430v1 Announce Type: new Abstract: Accurate prediction of multivariate time series requires models that simultaneously capture variable-specific dynamics and cross-variable interactions. In this work, a…
Generative Value ClassifierarXiv:2610.22497v1 Announce Type: new Abstract: Q-learning is premised on learning a function to predict the value of a state-action pair, with the goal of using such a function to guide policy improvement. Most approaches learn…
Generative adversarial networks with Monte Carlo dropout uncertainty quantification for structural health monitoring: Fibre Bragg grating dataarXiv:2610.22436v1 Announce Type: new Abstract: The signal generation capabilities of a novel data augmentation framework are examined in aerospace structures. First, the framework learns class-conditional temporal and spectral…
Lean4AgenticRL: Advancing Agentic RL with Verifiable Multi-level Process RewardsarXiv:2610.22448v1 Announce Type: new Abstract: Enhancing the agentic capabilities of Large Language Models (LLMs) to tackle complex software engineering (SWE) and general terminal-usage problems is a pressing challenge. Current…
Learning smooth dynamics via Kinematic InterpolantsarXiv:2610.22519v1 Announce Type: new Abstract: Inferring dynamics from real-world experimental data is inherently ambiguous, as many plausible dynamical systems can explain the same positional observations at measurement times…
Predicting Privileged Information Effectiveness for On-Policy Self-DistillationarXiv:2610.22512v1 Announce Type: new Abstract: On-policy self-distillation (OPSD) enables large language models (LLMs) to learn from privileged information (PI) without a separate teacher model. However, prior work largely…
Progressive Misalignment Can Emerge from Benign Recursive Self-DistillationarXiv:2610.22467v1 Announce Type: new Abstract: Training models on their own outputs has attracted widespread attention as a possible route to advance AI capabilities. One prominent approach is self-distillation, where a model is…
Rank Measures of Fine-Tuning Updates Need a Noise BaselinearXiv:2610.22438v1 Announce Type: new Abstract: Studies of what fine-tuning does to a language model often summarise the weight update $\Delta W$ by its rank. We compare the rank measures used for this against the same measures…
Sparse Autoencoders Can Induce Local Geometry for Mitigating Catastrophic ForgettingarXiv:2610.22439v1 Announce Type: new Abstract: Catastrophic forgetting remains a challenge in supervised continual learning, as adapting to new tasks causes representation drift and loss of previously learned information. This…
TRACE: Transformer Residual Activation Codebook Encoding for Communication-efficient Distributed Edge InferencearXiv:2610.22435v1 Announce Type: new Abstract: Distributed Transformer inference across co-located edge devices is fundamentally communication-bound, as exchanging activations between sequence-parallel partitions dominates…
Trust but Verify: Designing Region-Inhomogeneous Forward Dynamics for Discrete DiffusionarXiv:2610.22380v1 Announce Type: new Abstract: Continuous diffusion treats the forward process as a design space; discrete language diffusion often uses absorbing corruption, leaving context fully trusted throughout generation…
When is a large language model a good calibration agent? Physics-labeled prompting for budgeted engineering simulator calibrationarXiv:2610.22379v1 Announce Type: new Abstract: Calibrating expensive engineering simulators requires tuning model parameters to match reference data, a process heavily constrained by computational costs. This study investigates…
A woman was arrested in Philly for blocking a delivery robotCarolyn Marvin was arrested and charged with disorderly conduct after blocking the path of an Uber delivery robot and refusing to get out of the way. Marvin told Philadelphia's ABC13 "I know they're taking the jobs of human…
Meta removes language that may have allowed it to scrape news sitesAfter backlash, Meta is updating its terms again to remove language that suggested it could scrape content from sites, including news sites, to train its AI. Specifically, the following language no longer appears on the…
Websites are closing their doors to AI agentsAutonomous agents are the hottest thing in AI. OpenAI, Meta, Google, Instinct, and others promise their agents can scour the internet on your behalf, doing anything from booking a dinner reservation and cleaning out your inbox to…
Roundtables: A Conversation With the Creator of AI-Designed VirusesListen to the session or watch below Can AI design new life forms? In 2025, Stanford University PhD student Samuel King came up with a preliminary answer when he used a generative AI model to propose genetic blueprints for…
Democrats think cracking down on AI could give them an edgeDemocrats could win back control of Congress this November, and if they do, they'll need to decide how to approach one of the country's newest and thorniest political issues: AI. Polls predict Democrats will flip at least one…
The Download: failed social media bans, and extending pets’ livesThis is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology. Kids are outsmarting social media bans. That’s not a problem we need to solve. —Michal…
A week with RTX Spark: everything we’ve learned using Nvidia’s new laptopsNvidia's RTX Spark N1X processor is finally here, and we've been collectively testing a small fortune's worth of powerful laptops sporting this new "superchip." RTX Spark is designed to be a high-performing Arm-based SoC for…
Meta’s new terms may allow it to train AI on news sites for freeMeta's new terms appear to give it permission to crawl and scrape websites "associated" with the businesses that use its platforms - including online publishers, according to a report from Nieman Lab. The new terms, which go into…
Can’t bear to say goodbye to your pet? Biotech’s got you covered.I don’t remember much about Peppy, my first and only pet cat. I can conjure the sensation of stroking her while she purred, recall how she used to get stuck in trees (just like in cartoons!), and chuckle about the time she pooed…
Love is infrastructureI. Meet cute Barnabas and Mainspring grew up near at hand, about an hour apart with good traffic, but for a long time they weren’t close. They traded glimpses and occasional hellos and then went about their business. Both of them…
This implant can restore sight for patients with macular degenerationAge-related macular degeneration (AMD) affects more than 5 million people around the world. And until now, no treatment could restore their vision. The Prima system, which was approved in Europe in July and is awaiting FDA…
Kids are outsmarting social media bans. That’s not a problem we need to solve.Social media bans are stacking up. In July, France joined Australia in restricting minors from accessing social media—barring children under 15 from major platforms, before the ban was blocked by the country’s top court on human…
A Large-Scale Dataset for Multi-Class Financial News Classification in Brazilian PortuguesearXiv:2610.20630v1 Announce Type: new Abstract: The development of Financial Natural Language Processing (NLP) systems for Brazilian Portuguese is hindered by the scarcity of domain-specific datasets. To address this, we present…
APRiL: An Open-ended Benchmark for Chinese Social Awareness in Large Language ModelsarXiv:2610.20785v1 Announce Type: new Abstract: Large language models are increasingly used in social interactions, where appropriate responses require recognizing implicit cues, inferring mental states, identifying conflicts…
AbridgeKV: Compressing Long Reasoning into the KV Cache of Learned Pause TokensarXiv:2610.20641v1 Announce Type: new Abstract: Long chain-of-thought decoding is memory-bound: the KV cache of the generated tokens grows linearly with the test-time compute being spent. Evicting cache entries does not fix this…
CoTS: Competitive Token Selection for Latent Reasoning in Large Language ModelsarXiv:2610.20642v1 Announce Type: new Abstract: Recent latent reasoning methods move beyond discrete Chain-of-Thought (CoT) by replacing sampled tokens with continuous soft embeddings or hidden states, enabling richer…
Context Injection and Long-Horizon Reliability: Separating Duplicate Recognition, Local Processing, and Counter TrackingarXiv:2610.20633v1 Announce Type: new Abstract: Long-horizon failures of language models are usually measured as end-task success or as a horizon length. We instead score, step by step, three components of a 400-step ledger task…
DeepUnfolding_Agent: A Classical_Quantum Adaptive Control APIarXiv:2610.20615v1 Announce Type: new Abstract: Adaptive optimization workflows in machine learning, federated learning, quantum machine learning, and hybrid classical quantum systems often embed controller logic directly inside…
Does Personalization Break Trust? Open-Set Rejection Calibration Under Few-Shot On-Device Intent AdaptationarXiv:2610.20652v1 Announce Type: new Abstract: Always-on virtual assistants increasingly personalize on-device to new user-specific commands via few-shot fine-tuning (e.g., LoRA), but this adaptation is evaluated almost…
Exploring the Design Space of Permutation Diffusion LLMsarXiv:2610.20635v1 Announce Type: new Abstract: Permutation generation with language models requires both text-conditioned ranking and a global one-to-one assignment between candidates and output positions. We study this problem…
Jev-as-a-Judge for RAG Claim Verification: Confidence-Gated Cascading Between a Non-Generative Verifier and a Frontier LLMarXiv:2610.20634v1 Announce Type: new Abstract: Retrieval-augmented generation asks one question at volume: does this evidence support this claim? The answer is one bit, yet most pipelines obtain it from a text generator and pay…
MeddeX: A Retrieval-Augmented LLaMA-3 System with Gemini Vision for Evidence-Backed Medical Report AnalysisarXiv:2610.20632v1 Announce Type: new Abstract: Modern healthcare generates increasingly complex medical reports that challenge clinical professionals in terms of time and interpretive burden. Manual review processes are slow…
PRISM: PRIvileged Sibling-guided Multi-Agent Topology DesignarXiv:2610.20628v1 Announce Type: new Abstract: Multi-agent systems (MAS) based on large language models (LLMs) have become a powerful way to address complex problems, and their effectiveness depends critically on the…
PRISM: Transfer and Limits of Activation Interventions in Tool-Calling Language ModelsarXiv:2610.20808v1 Announce Type: new Abstract: Recent literature shows that unsafe tool calls can often accompany textual refusals in language models. To investigate this hidden vulnerability, we introduce PRISM, a framework for…
Real-time Chatbot Romance Scam Detection in Stage ClassificationarXiv:2610.20631v1 Announce Type: new Abstract: Romance scam has become a serious problem via social media, and the improvement of artificial intelligence enable to fake identify easily. In the study, a chatbot has developed to…
Reference-Guided Turn-Taking Style Transfer for Full-Duplex Spoken Language ModelsarXiv:2610.20763v1 Announce Type: new Abstract: Full-duplex spoken language models decide at every frame whether to take the floor, defining a conversational personality -- yet each set of weights encodes exactly one, which human…
Verdict: Encode Once, Decide ManyarXiv:2610.20778v1 Announce Type: new Abstract: Automating organizational work means answering many small typed questions about one piece of state (does this email need a reply, how urgent is it, who owns it) with probabilities…
Causal Syntax Circuits in CodeLMs: Budget and Probe Decide What Looks LocalisedarXiv:2610.20683v1 Announce Type: new Abstract: Code models write Python when the prompt does not say which language to use. We ask a mechanistic question about that habit: is it produced by a small, findable group of components…
Diminishing Returns of Data in Sparse Autoencoders: Functional Behavior does not Guarantee Feature ReproducibilityarXiv:2610.20680v1 Announce Type: new Abstract: Sparse autoencoders (SAEs) are typically trained on hundreds of millions to billions of activation tokens, yet little work has tested whether this scale is necessary. We study how…
Expanding Attention: A Taylor-Series Route to Linear-Time Transformers with a Fixed Number of Recurrent StatesarXiv:2610.20637v1 Announce Type: new Abstract: We expand the exponential kernel of attention into a truncated Taylor series of $n$ terms and factorize each term into a tensor-power inner product, which collapses the causal…
Feature Elicitation for SAE Steering of Deceptive Behaviour in Small LLMsarXiv:2610.20638v1 Announce Type: new Abstract: Research on deceptive alignment is becoming increasingly urgent as frontier-model capabilities advance and their risk of causing catastrophic harm increases. Alignment faking is a…
FlowBudget: Training-Free Sampling-Budget Estimation for Flow Matching ModelsarXiv:2610.20636v1 Announce Type: new Abstract: Sampling from continuous flow-based generators such as flow matching models requires numerical ODE or SDE integration, making inference cost depend on the number of function…
Interpreting Language Model ParametersarXiv:2610.20748v1 Announce Type: new Abstract: Mechanistic interpretability aims to uncover how neural networks use their parameters to implement their impressive neural algorithms. Although previous work has uncovered…
KNOU-Flood: Advancing global streamflow forecasting with lead-aware probabilistic machine learningarXiv:2610.20640v1 Announce Type: new Abstract: Global streamflow forecasting supports flood preparedness, yet data-driven models trained on reanalysis lose skill when driven by operational forecasts, increasingly so with lead…
Learning Topology-Aware Representations for Mechanics-Relevant TPMS MetamaterialsarXiv:2610.20684v1 Announce Type: new Abstract: Learning informative representations of mechanical Triply Periodic Minimal Surface (TPMS) metamaterials is important for mechanics analysis and structural design, yet existing…
On-Policy Residual Learning for Diffusion Language ModelsarXiv:2610.20687v1 Announce Type: new Abstract: Residual context is key to unlocking the speed-quality Pareto frontier of diffusion language models (DLMs) by carrying forward predictive distributions across denoising steps. Yet…
Quantile-Guided Diffusion for Probabilistic Time-Series ForecastingarXiv:2610.20739v1 Announce Type: new Abstract: Quantile forecasts summarize uncertainty at each future time step, while diffusion forecasters represent it through sampled future trajectories. We study how predicted quantiles can…
RoLaQ: Joint Rotation and Range Calibration for 2-Bit KV Caches in Multi-Head Latent AttentionarXiv:2610.20686v1 Announce Type: new Abstract: Multi-head latent attention (MLA) compresses the content of a key-value cache into a shared latent per token, making low-bit storage attractive for long-context inference. At two…
Same Answer, New Box: How Much of RLVR's Out-of-Domain Gain Is Answer Format?arXiv:2610.20639v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) is credited with gains beyond the domain its rewards check, such as higher MMLU accuracy after training on mathematics. Such…
Spectral Indistinguishability and Learning-Curve Identifiability in Quadratic NetworksarXiv:2610.20678v1 Announce Type: new Abstract: We study what spectral summaries and scalar learning curves reveal about centered quadratic networks. We construct analytic positive input densities with exactly Gaussian one- and…
TurboMamba: Faster Inference, Faster Training, and Better Prediction with Lexical MemoryarXiv:2610.20682v1 Announce Type: new Abstract: We introduce TurboMamba, a language-model architecture for faster inference, faster training, and better token prediction. A global Mamba-3 model runs once per completed token…
Vertical Sliced Wasserstein Distances for Meta-MeasuresarXiv:2610.20743v1 Announce Type: new Abstract: Many modern learning problems require comparing probability distributions whose individual observations are themselves probability measures, naturally giving rise to meta-measures…
ChatGPT can peek at your Chrome tabs nowOpenAI's ChatGPT Atlas browser is gone, but now ChatGPT's Google Chrome extension is getting some upgrades that allow it to use the browser tabs you already have open. With the extension installed, OpenAI says ChatGPT can now…
Sega pulls Total War: Shogun 2 remaster from sale following disastrous launchSega is removing Total War: Shogun 2 - Complete Edition from storefronts following a disastrous launch where users complained about issues like bugs and upscaling that appears to have been done by AI. Complete Edition, a remaster…
The tech backlash is now in theatersThough movies about disruptive tech founders are nothing new, 2026 has been unusually stacked with features that take a much more critical look at how Silicon Valley is reshaping our reality. Aaron Sorkin's The Social Reckoning…
Trump posts AI-edited photo to brag about White House restoration workPresident Donald Trump posted a series of photos on Truth Social showing off renovations to the White House - but one of them appears to be modified with AI. The picture, which compares an old White House column to a "restored"…
Bluesky’s AI tool now lets you make games and apps to share on socialBluesky's Attie AI tool, which initially launched earlier this year as a way to use AI to build your own feeds, now lets you make "small" social apps like games, polls, and dashboards that you can then share with others as their…
Meta and Apple team up to make Muse AI models run better on MacsMeta announced the Muse Spark Open AI model today, claiming that it's the "most capable US open-weight model to date." But the company also says that it's the "the first model in its class" that can "run on your desktop using two…
Friends don’t let friends feed their data to AI agentsThere's a growing trend in the consumer tech world: gadgets designed to spy on everything and everyone around you, regardless of whether or not anyone else actually consented to it. Now, with the advent of "AI personal…
The Download: reviving frozen pig kidneys and boosting nuclear powerThis is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology. Pig kidneys that were “frozen” for a year have been brought back to life Pig kidneys that…
How Windows is being optimized for Nvidia’s RTX Spark laptopsMicrosoft and Nvidia held a launch party for the first wave of RTX Spark laptops last week in San Francisco, where a new wave of AI PCs took center stage amid a packed crowd and a lively hands-on area. A day after the media…
Nobody is safe from celebrity AI deepfakesIn hindsight, the post on Instagram should have raised more red flags. The image purported to show actress Mia Goth, just days after filing for divorce from actor and filmmaker Shia LaBeouf, posing in a T-shirt with a pointed…
How much more can nuclear power plants give?In this age of rising electricity demand, people are trying to squeeze every last bit of power out of every power plant possible. Over the past few weeks, there’s been big news about nuclear power plants trying to do just that…
Benn Jordan on Flock, privacy, and the new surveillance backlashToday, I’m talking with Benn Jordan, musician, YouTuber, researcher, and investigative journalist. You might know Benn from those first two titles — he’s got a prolific discography of experimental music dating back decades. But…
Six wild ideas for perpetuating your mindHave you ever thought about what makes you you? Science assures us it has everything to do with the three-pound organ between our ears, with its billions of neurons and trillions of delicate connections. But it’s a lot trickier…
Pig kidneys that were “frozen” for a year have been brought back to lifePig kidneys that were cooled to -150 °C and stored in a freezer for months have been successfully rewarmed and shown to work again for the first time, say scientists. They hope to replicate the findings with human organs. The…
Google launches its ‘universal’ online shopping cart ahead of the holidaysGoogle's intelligent AI shopping cart is finally here, and just in time to tempt users into Black Friday and seasonal holiday spending. The Universal Cart tool Google previewed at its I/O event in May is now rolling out in the US…
Your secrets aren’t safe with this cute robot toy — they’re on Chinese servers ready to be hackedThere's a new digital pet in town - a cute little marshmallow of a robot that can change its cartoony expressions to match your mood. But if you or your kids talk to "Eiliko" over Wi-Fi, it'll phone home to China. Its AI…
CAFE: Confining Feature Distillation to Language-Routed Adapters for Compact Multilingual Automatic Speech RecognitionarXiv:2610.19134v1 Announce Type: new Abstract: Feature distillation is usually expected to add to logit distillation. We find that this expectation does not hold for two common feature losses in compact multilingual automatic…
Can LLMs Access their World Knowledge for Event Prediction?arXiv:2610.19021v1 Announce Type: new Abstract: Recent work has questioned whether large language models (LLMs) can be useful for temporal event prediction. Despite vast pretrained world knowledge, LLMs often underperform simpler…
Crossing the Gender Binary: Modelling Gendered Reference in Science Fiction and General FictionarXiv:2610.19028v1 Announce Type: new Abstract: Science fiction is widely credited with unsettling gender. This article asks whether that holds at the linguistic level, in how readily gendered reference gives way to its…
DecisionRobust: Benchmarking Robustness for JEV Style Decision Models Across Text and VisionarXiv:2610.19118v1 Announce Type: new Abstract: Emerging decision models such as JEV provide typed interfaces that map task instructions and observations directly to choices, judgments, and scores. As these models are…
Evaluating Large Language Models for Multilingual Abstractive Summarization: A Comprehensive Study of English and BengaliarXiv:2610.19003v1 Announce Type: new Abstract: Abstractive summarization remains challenging across languages, where linguistic quality and factual consistency may diverge, particularly in low-resource settings. We present a…
Fantastic Metrics and How to Find Them: Meta-Evaluating Metrics for Multi-lingual Style-Personalized GenerationarXiv:2610.19166v1 Announce Type: new Abstract: Meta-evaluation of text generation metrics and LLM-judges is primarily conducted using metric-human correlations. However, prior work has shown that correlation is not an…
Following the Flow the Law Requires: Training Voice Agents to Transfer to Unseen Regulated Procedures in Debt CollectionarXiv:2610.18881v1 Announce Type: new Abstract: Voice agents built on large language models (LLMs) now handle customer calls, but in regulated applications completing the task is not enough: the agent must follow a conversational…
From Copying to Composition: How Language Models Develop In-Context LearningarXiv:2610.19113v1 Announce Type: new Abstract: In-context learning (ICL) allows language models to adapt their behavior from instructions and demonstrations in a prompt, but accuracy alone does not reveal how contextual…
From Qualitative Text to Integrated Evidence: The Parallel-Then-Integrated (PTI) ProcedurearXiv:2610.19164v1 Announce Type: new Abstract: Mixed methods research offers established strategies for integrating qualitative and quantitative evidence, but less guidance for integrating two computational representations of…
HERO: Harnessing Evidence for Test-time Refinement and Prompt Optimization in Program GenerationarXiv:2610.19184v1 Announce Type: new Abstract: Harness optimization improves LLMs by refining reusable prompts and scaffolding, yet requires further adaptation for program generation tasks such as text-to-SQL and text-to-Python…
How to Evaluate When You Don't Know How to Evaluate? Choosing Reliable Setups for Base Language Model BenchmarkingarXiv:2610.19185v1 Announce Type: new Abstract: Evaluation of large language models (LLMs) remains largely pre-scientific: it involves many design decisions, with little guidance on how to make them. These choices can…
Joint Subspace Sparse Attention for Efficient Long-Context DecodingarXiv:2610.19026v1 Announce Type: new Abstract: Sparse attention reduces the KV-cache traffic that dominates long-context LLM decoding, but practical methods largely operate at coarse granularity. Token-level selection offers…
NEPSEE: A Double-Annotated Benchmark for Nepali Sentiment AnalysisarXiv:2610.19190v1 Announce Type: new Abstract: Many sentiment datasets use one annotator for each item, so the test labels show the conventions of that person. We build a Nepali benchmark from two annotators who labelled the…
Pre-Trained Language Models as Zero-Shot Tools for Social Science ResearcharXiv:2610.19048v1 Announce Type: new Abstract: Record linkage and demographic inference from names are routine demands in social science. Most approaches to these problems require labeled training data that are difficult or…
Similar Models, Broken Odds: Where Luce's Axiom Fails in Chatbot ArenaarXiv:2610.19095v1 Announce Type: new Abstract: Chatbot Arena ranks language models with the Bradley-Terry model, which gives each model one score and so assumes Luce's choice axiom. Choice theory predicts where this fails…
Data Density Scaling Laws for Image Self-DistillationarXiv:2610.19013v1 Announce Type: new Abstract: Current scaling law formulations suggest that increasing the number of unique samples in a dataset improves model performance, while repeated exposure to the same samples provides…
Do Perturbation Predictors Learn Gene Interactions? Diagnosing Extrapolation in Agentic ScreeningarXiv:2610.18880v1 Announce Type: new Abstract: High-throughput perturbation screens increasingly use machine-learning models to predict the effects of gene combinations that were never measured. A difficult case arises when both…
Do Vision CIL Methods Transfer to Protein? A Diagnostic Benchmark of Frozen Protein EncodersarXiv:2610.18879v1 Announce Type: new Abstract: Protein function annotation operates over an expanding label space, making class-incremental learning (CIL) a natural framework for incorporating newly discovered functions without…
Graph Coarsening Enables Escaping Local Optima in Compute-Constrained Nonconvex MAX-CUTarXiv:2610.19043v1 Announce Type: new Abstract: Because its binary optimization landscape contains exponentially many local optima, MAX-CUT is highly sensitive to initialization. We study Particle Polynomial Relaxation (PPR), a…
How Many Ranks Does a Token Need? A Noise-Floor Squelch for Rank-One LoRA ExpertsarXiv:2610.19033v1 Announce Type: new Abstract: Low-rank adaptation (LoRA) applies every rank-one component of its update to every token, and mixture-of-experts variants replace this with a learned router that activates a fixed…
IR-PRM+ with Previous-Utility Prediction: Constant Regret and Best-Iterate ConvergencearXiv:2610.19016v1 Announce Type: new Abstract: Regret matching (and its variants) and counterfactual regret minimization are central algorithms in practice for normal-form and extensive-form game solving. Yet these have…
Inverse Reasoning Models for Efficient Post-Training and Verification from Answer-Only DataarXiv:2610.18878v1 Announce Type: new Abstract: Post-training reasoning LLMs often requires making a tradeoff between costly supervision and compute inefficiency: supervised finetuning typically requires reasoning traces, which…
Lag: A Mean-Field Optimal Policy for Online Assignment with Reusable ResourcesarXiv:2610.19038v1 Announce Type: new Abstract: We study online task assignment with reusable resources. This problem arises in peer reviewer assignment, skill-based call routing, rideshare matching, emergency dispatch, and…
Loss Curvature as a Sampling-Free Proxy for Memorization in Diffusion ModelsarXiv:2610.19042v1 Announce Type: new Abstract: Understanding the mechanism behind why diffusion models memorize their training data remains an open question in generative modeling. In this paper, we examine this question from…
Lotus: Learning to Understand Time-series by Learning to ForecastarXiv:2610.18877v1 Announce Type: new Abstract: Time-series language models typically align numerical signals with language using labels, captions, or question-answer pairs. Although such supervision encourages linguistic…
PMO-Dock: Benchmarking Docking, Specificity, and Generalization in Molecular OptimizationarXiv:2610.19011v1 Announce Type: new Abstract: The Practical Molecular Optimization (PMO) benchmark standardized evaluation in molecular optimization, but it is built on simple property-based oracles that do not capture…
Scaling Cheap Synthetic Pretraining Improves Indoor Radio-Map PredictionarXiv:2610.19015v1 Announce Type: new Abstract: Real measurements are too limited to train an accurate indoor pathloss predictor that works across a wide range of buildings. Large-scale synthetic pretraining offers a way forward…
Token Utility for On-Policy Distillation via Local Trust-Region OptimizationarXiv:2610.18883v1 Announce Type: new Abstract: Token-selection methods for on-policy distillation (OPD) prioritize student-visited positions using diverse signals, including uncertainty, teacher-student disagreement, and…
Tracing Morphology, Semantics, and Divergence in Language AcquisitionarXiv:2610.19041v1 Announce Type: new Abstract: Understanding the dynamics of language acquisition in Large Language Models (LLMs) is crucial for uncovering how statistical representations evolve into structured linguistic…
Who Should We Listen to More? Welfare-Aware Preference Acquisition for Pluralistic AlignmentarXiv:2610.19035v1 Announce Type: new Abstract: Pluralistic alignment needs to accommodate diverse preferences under limited human feedback. Using AI simulators to label preference comparisons reduces annotation costs, but…
McKinsey is making job applicants spar with a fake AI clientConsulting firm McKinsey & Company is going to ask some entry-level candidates to have a 10-minute conversation with an AI simulation of a client as part of the interview process, according to The Wall Street Journal. The AI…
Amazon’s always-listening Bee wearable can now help you buy stuffLast year, Amazon bought Bee, a relatively unknown startup with a $50 always-listening AI wearable that summarized every conversation you had. Today, the e-commerce giant is announcing two new Bee devices - and a new subscription…
Eight states sue OpenAI, saying ChatGPT isn’t safe for kidsOpenAI is facing a new wave of lawsuits from eight US states that accuse the company of harming children and misleading customers about the safety of ChatGPT, as reported earlier by Reuters. The lawsuits, filed separately by…
The AI race is back onLast week, Anthropic and OpenAI looked like they had the AI race to themselves, pulling ahead with increasingly powerful models that left their rivals in the dust. Google seemed hopelessly far behind, while Meta, despite spending…
Now that Character.AI is going bankrupt, what happens to all of its users’ data?New York Attorney General Letitia James revealed a years-long multi-state investigation against Character.AI as they now seek to require protections on consumer data sold through its bankruptcy proceeding. James is among 40…
YouTube sticks new labels on AI-generated songsYouTube is adding a "Made with AI" label to tracks that were "altered or fully generated" using AI, with a similar approach to its existing process for applying AI labels to videos. It doesn't sound like this will apply to any…
My AI doppelganger tells me what to eatThis is Optimizer, a weekly newsletter sent from Verge senior reviewer Victoria Song that dissects and discusses the latest gizmos and potions that swear they're going to change your life. Opt in for Optimizer here. For the past…
OpenAI claims an ex-employee took its product plans and presented them to AppleOpenAI claims a former employee took more than 100 files related to its product plans before joining Apple. In a document filed on Wednesday, OpenAI accuses the unnamed employee of sending this information to a personal account…
The Download: faking blood and the future of batteriesThis is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology. The US military’s race to make fake blood In February 2007, a US military helicopter…
Microsoft has a new machine learning tool to improve weather forecastsOld-school physics-based weather forecasting and even new AI models typically become less reliable beyond two weeks, a problem Microsoft claims to have solved using machine learning. Researchers with the company say they've found…
Anthropic’s self-replicating AI warning is an alarming deja vuAre legions of smart devices - fridges, ovens, vacuum cleaners, lawnmowers, security cameras, and TVs - conspiring to take over the internet? No. But they could soon be unwitting hosts to self-replicating AI models that spread…
Android is using AI to suss out scammers in Google MessagesAndroid is introducing new scam defense features that aim to make it easier for users to evade mobile fraud, including bolstered protection in Google Messages and additional safeguarding tools. Building on the Scam Detection…
Epic’s new games launcher is ‘vibe coded’Epic Games is announcing a big refresh of its PC games launcher today in preview, saying that the new version is "way faster" and now supports Linux. But the company, which has been publicly making a big push into AI-assisted…
The US military’s race to make fake bloodIts call sign was Morphine 1-2. In February 2007, the hulking dual-rotor casualty evacuation helicopter had just flown three wounded soldiers to a field hospital in Balad, north of Baghdad, when another call came: an emergency…
ASSET: Adaptive Speech Segmentation via Reinforcement LearningarXiv:2610.14309v1 Announce Type: new Abstract: Speech large language models (LLMs) are often built using pretrained acoustic encoders as an audio interface to an LLM decoder. However, LLMs scale poorly with input sequence…
Agentic Data Engineering for LLMs: System Design and a Controlled Empirical StudyarXiv:2610.14238v1 Announce Type: new Abstract: LLM data engineering requires iterative experimentation to determine how data selection, rewards, and curricula affect model learning, making it a natural setting for AI-for-AI…
Does System One Transfer? Calibrated Typed-Decision Models, Label Budgets, and Translation for Indonesian Regional LanguagesarXiv:2610.14112v1 Announce Type: new Abstract: Calibrated typed-decision ("System One") models return a label and a probability in a single forward pass at a small fraction of the cost of large language models (LLMs), yet their…
Evaluating LLMs as Agentic Workflow Executors in Real-World Customer Support SkillsarXiv:2610.14346v1 Announce Type: new Abstract: Enterprise customer-support agents increasingly rely on Large Language Models (LLMs) to execute bounded, tool-using workflows. We study this problem through the lens of Skill LLMs…
Fin_Agent at FinEval 2026: Task-Aware Methods for Multilingual Financial NLParXiv:2610.14101v1 Announce Type: new Abstract: We present Fin_Agent, our submission to the FinEval 2026 shared task on multilingual fi nancial language understanding. Our sys tems address Greek financial named-entity…
Is the Future Predictable? Modeling Future Predictability for Reliable Temporal ReasoningarXiv:2610.14073v1 Announce Type: new Abstract: Large language models (LLMs) remain unreliable when reasoning about the future. Existing models often overlook the difference among future states, committing to specific answers…
Loose Lips: Understanding Privacy Leakage in Agentic DialoguearXiv:2610.14071v1 Announce Type: new Abstract: As LLM agents are increasingly deployed in high-stakes enterprise settings, understanding how they handle sensitive information in agentic dialogue has become critical. Privacy…
Modeling the Arrival Time of Information-Bearing Events in Natural LanguagearXiv:2610.14212v1 Announce Type: new Abstract: Understanding how information is distributed over time is fundamental to modeling natural language. While existing empirical studies primarily rely on post-hoc analysis of…
Multimodal Co-Generation With Continuous Bitstream DiffusionarXiv:2610.14349v1 Announce Type: new Abstract: We show that continuous bitstream diffusion (CoBit), originally developed for language modeling, provides a unified framework for joint and conditional multimodal generation using…
Neither True nor False: Do LLMs Represent Truth-Value Gaps in Plural Predication?arXiv:2610.14438v1 Announce Type: new Abstract: Do Large Language Models (LLMs) genuinely grasp the truth conditions of plural descriptions, or do they force every sentence into true or false? We investigate the Homogeneity Gap…
Next-Concept Modeling: Fast, Parallel Coarse-to-Fine Text GenerationarXiv:2610.14162v1 Announce Type: new Abstract: Diffusion language models (DLMs) offer parallel sampling for faster generation than autoregressive models, an increasingly important advantage as inference becomes a dominant…
PsyBer-Agent: A Psychology-Driven User Agent for Recommender SystemsarXiv:2610.13989v1 Announce Type: new Abstract: Evaluating recommender systems before deployment requires simulators that remain realistic over long, closed-loop interaction cycles. Current LLM-based agents generally function as…
Scaling Laws for Multimodal Data MixturesarXiv:2610.14423v1 Announce Type: new Abstract: Frontier AI systems are increasingly natively multimodal, jointly pretrained on multiple modalities, such as text, vision, and audio. However, the scientific understanding of the…
SciCurateBench: Curating Experimental Data from Heterogeneous Scientific Literature with Verbal-Action AgentsarXiv:2610.14393v1 Announce Type: new Abstract: Scientific research increasingly depends on curating experimental data from literature. Scientific data curation requires verifying exact experimental conditions (e.g., specific…
The Thinking Leakage in Reinforcement Learning for LLMsarXiv:2610.14270v1 Announce Type: new Abstract: Hybrid reasoning models such as the Qwen3 series switch between a THINK mode and a NO-THINK mode through a few chat-template tokens. A popular recipe trains such models with…
Coding LLMs Can Be Harnessed to Learn Interpretable Models from DataarXiv:2610.14006v1 Announce Type: new Abstract: Since compact, interpretable classifiers correspond to simple programs, it is natural to ask if LLM-based coding agents can be used to learn interpretable models from data. In this…
DoSA: Dots Sparse AttentionarXiv:2610.13990v1 Announce Type: new Abstract: Sparse attention visits few keys, yet finding them can still require scoring every key with every indexer head. We introduce DoSA (Dots Sparse Attention), a lossless method for…
Enhanced Trading Systems with Intelligent Market AnalysisarXiv:2610.13998v1 Announce Type: new Abstract: This paper proposes a hybrid reinforcement learning trading framework integrating intraday market data with transformer-based financial sentiment signals. The system extracts…
GameSmith: Scaling Zero-Sum Self-Play with Synthesised GamesarXiv:2610.13995v1 Announce Type: new Abstract: Post-training large language models (LLMs) on two-player zero-sum games provides a verifiable reward, and the gains have been shown to transfer to general reasoning. Existing…
LACRM: LLM-Guided Mining of Directed Advertiser Competition Relationships in E-Commerce AdvertisingarXiv:2610.13959v1 Announce Type: new Abstract: In e-commerce advertising, ad platforms typically fail to model the externalities among advertisers when making optimization decisions: an advertiser's actual performance is largely…
MDN-VJEPA: Multimodal Probabilistic Joint-Embedding World ModelsarXiv:2610.13956v1 Announce Type: new Abstract: Joint-Embedding Predictive Architectures (JEPAs) learn world models by predicting future representations rather than reconstructing observations. Variational JEPA (VJEPA) gives this…
MRFlow: Mechanism-Structured Residual Flow Matching for Virtual Cell Perturbation PredictionarXiv:2610.13966v1 Announce Type: new Abstract: Predicting cellular responses to chemical and genetic perturbations is a central test for AI virtual cells, yet many single-cell models reduce each condition to an average…
PRIME: Frequency-Aware Unified Pruning and Merging for MoE CompressionarXiv:2610.13982v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) models have emerged as an effective paradigm for scaling large language models, yet their massive parameter footprint poses severe memory challenges for…
Posterior Flow MatchingarXiv:2610.13994v1 Announce Type: new Abstract: Flow matching learns how to transport noise toward data, but its mean prediction does not directly report the endpoint uncertainty remaining at an intermediate state. This paper…
PreSO: Privileged Representation Isolation for On-Policy Self-DistillationarXiv:2610.14001v1 Announce Type: new Abstract: On-policy self-distillation (OPSD) uses a self-teacher conditioned on privileged information to turn the sparse outcome signal of reinforcement learning with verifiable rewards…
Predict Before You Modify: Learning Improvement Dynamics for Self-Evolving AgentsarXiv:2610.13991v1 Announce Type: new Abstract: Self-evolving agents improve through repeated cycles of modification and evaluation. However, existing methods receive feedback on modifications only after costly evaluations, and…
SemTree: Judge-Aware Semantic Decision Trees for Inspectable and Repairable Rule DecisionsarXiv:2610.13999v1 Announce Type: new Abstract: Rule decisions such as content moderation, advertising compliance, and eligibility checks combine several conditions, exemptions, and missing-information cases, and an error can be…
Showing versus Doing: Teaching by DemonstrationarXiv:2610.14004v1 Announce Type: new Abstract: People often learn from others' demonstrations, and inverse reinforcement learning (IRL) techniques have realized this capacity in machines. In contrast, teaching by demonstration…
Splicing Hints into Reasoning Traces: Learning from Demonstrator FailuresarXiv:2610.13996v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards improves mathematical reasoning when a final answer can be checked, but a correct answer does not certify the derivation behind it…
VH-GPO: Verified Handoff for LLM Agent Reinforcement LearningarXiv:2610.14000v1 Announce Type: new Abstract: Group-relative reinforcement learning methods such as GRPO train large language model (LLM) agents by comparing rollouts for the same task. When every trajectory in a group fails…
OpenAI employee arrested for allegedly planting a bug in a conference roomAn OpenAI engineer was arrested after the company said it discovered a "sophisticated recording device" hidden in one of its offices. The employee, 35-year-old Abdulrahman Alfozan, is charged with using or attempting to use a…
Shopify opens its catalog up to more AI agentsMore AI agents will soon be able to browse and purchase from Shopify listings, marking an expansion of the company's agentic commerce ambitions. Shopify announced Tuesday it will let shoppers configure their AI agents to purchase…
Square’s new kiosk lets you talk to AI for help with your orderSquare is launching new hardware: a big kiosk for ordering things that has a touchscreen and lets you talk to an AI. It's called the Square Kiosk. Square says the Kiosk, which has a large pill shape, has an "agentic…
Xbox is officially embracing the chaos of AI-powered game portsRetro gaming is going through a wild time at the moment, thanks to decompilations and recompilations that are letting gamers port classic titles to new devices, or merge code from two different games into a single new experience…
Facebook will let you customize your feed algorithm using AIFacebook's new "Your Algorithm" feature will let you directly add and manage topics you want to see in your feed and Facebook Reels. Meta says your recommendations "respond right away" after you make updates using the new feature…
Google makes it easier to launch your vibe-coded appsThe next time you vibe-code a custom app with Google's AI Studio, you won't have to connect your phone to a computer to install it. On Tuesday, Google announced a new feature in the US that will allow you to launch personal apps…
Actress Mia Goth says it’s ‘incomprehensible’ that Instagram allowed an AI image of her to spreadEarlier this month, news broke that actress Mia Goth had filed for divorce from actor and filmmaker Shia LaBeouf. An Instagram post from the account miagoth_ - marked with a blue verified checkmark - quickly spread. The post…
The Download: open model trade-offs and geothermal power’s promiseThis is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology. Open models have real benefits. Do they outweigh the risks? Anthropic recently released a…
Epic shifts to ‘AI-accelerated development’ for upcoming Disney gameEpic Games plans to use AI to generate code and art for an unannounced Disney game, which is now delayed from its original March release window, according to a report from Bloomberg. The project's developers have been given an…
Open models have real benefits. Do they outweigh the risks?MIT Technology Review Explains: Let our writers untangle the complex, messy world of science and technology to help you understand what’s coming next. You can read more from the series here. Late last month, Anthropic released a…
DLSS 5 gets toned down for its Hogwarts Legacy debut next monthWhen Nvidia originally showed off DLSS 5 earlier this year, the technology immediately got branded as gen AI for video games. To gamers, Nvidia had lost the plot. I personally couldn't get over how faces were transformed using…
AI labs are buying data from dead startups to train their modelsWhen Keelan Miskell began winding down his crypto startup this year, he didn’t think its data was worth much: the users were anonymous, the company just a few years old. But he’s since turned the firm’s digital archives into real…
Apple launches HomeView, its first smart display for the homeIt's finally here: Apple's long-rumored smart display, the Apple HomeView, has arrived. I got a first look at the device in New York City this week, and it's gorgeous. The HomeView puts a small, vibrant screen atop a speaker base…
Google finally releases Gemini 4 ArgonAfter months sitting on the sidelines of the frontier AI race, Google has finally launched its long-awaited Gemini 4 Argon model, claiming it can compete with the best the industry has to offer. Google says Argon delivers…
Character.AI files for bankruptcyCharacter.AI, one of the first breakout startups of the generative AI boom, has filed for bankruptcy and is selling some of its assets to Disney. The company, which builds various online bots for users to chat or roleplay with…
I don’t miss the camera on the Ray-Ban Meta Audio glassesThe other day I whizzed past several people while running in the park, my playlist blasting at full volume. The next morning, I smiled at a barista while ordering a caramel apple-flavored matcha latte. Afterward, I sat on a park…
The Download: moon city problems and drone traffic controllersThis is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology. Mars may be a hellhole, but the moon is not far behind The US and China are racing to build…
Mars may be a hellhole, but the moon is not far behindWelcome to the second space race. You can be forgiven for experiencing déjà vu. Last time, it was the Soviet Union and the United States vying to be the first to plant some flags. Now it’s a sprint to the lunar surface between…
The ecologist revealing the invisible networks that revive rainforestsIn a research station in central Panama, you can walk through a century of forest time, watching scrubby plots of adolescent trees give way to cathedral-like canopies of mature growth. Forest ecologist Daisy Dent, a senior…
Meta has some Wonder Full new AI modelsMeta is making up for lost time in the AI race. After launching Muse Spark, the first model from its revamped Superintelligence Labs division, and buzzy AI agent Muse, it's now launching two new models it claims can go toe-to-toe…
Microsoft’s new AI chip makes it less reliant on Nvidia’s GPUsMicrosoft is announcing its third-generation Maia in-house AI chip today, designed to be the "primary AI inference system" for Microsoft's products and services. Maia 300 not only improves the cost and efficiency of running AI…
Activating the Annotator: Operationalising Lived Experience in Data AnnotationarXiv:2610.12701v1 Announce Type: new Abstract: Perspectivist NLP has established that annotator positionality shapes labels for subjective tasks, but the field still lacks methods for operationalising it. Positionality is…
AutoIndexer: Flexible-Order Decoding by Training Causal Models on Chains of EditsarXiv:2610.12545v1 Announce Type: new Abstract: Autoregressive decoding is less suited to non-causally ordered data, e.g., cross-references or future dependencies, since their outputs cannot be revised post hoc, unlike iterative…
CLUE: A Contrastive Learning Framework for Unsupervised Event Type Induction and AnnotationarXiv:2610.12580v1 Announce Type: new Abstract: Event ontology is the foundational framework for defining events in a dataset. Event type induction generally involves domain experts who define guidelines for creating event types…
Contextual Correction of Parallel Draftsfor Speculative DecodingarXiv:2610.12570v1 Announce Type: new Abstract: Speculative decoding accelerates large language model inference by using a lightweight drafter to propose multiple tokens that are subsequently verified in parallel by the target…
DistressBench: Evaluating Multi-Dimensional Crisis Support in Large Language ModelsarXiv:2610.12758v1 Announce Type: new Abstract: Language models have been adopted faster than evaluation practices that reliably assess their risks, and a growing share of use is affective rather than informational. Within that…
GeoFitBench-LLM: A Benchmark for Assessing Large Language Models' Capabilities in Geospatial Data Requirements Elicitation for Geo-Analytic TasksarXiv:2610.12669v1 Announce Type: new Abstract: Large language models are becoming central to GeoAI systems, yet their evaluation rarely considers the elicitation of geospatial data requirements. This omission is critical as…
GeopoliticalQA: Benchmarking Retrieval and Generation over Intelligence ReportsarXiv:2610.12617v1 Announce Type: new Abstract: Geopolitical and strategic intelligence reports constitute a rich source of expert knowledge and have increasing value in the current political climate, but their heterogeneity and…
MADS: Multi-Agent Dialog Simulation for Robust Conversational AgentsarXiv:2610.12757v1 Announce Type: new Abstract: Task-oriented conversational agents remain fragile under realistic conditions, especially when users exhibit non-cooperative behavior. Existing function-calling benchmarks…
One Model to Loop Them All: Elastic Latent Recurrence for Language ModelsarXiv:2610.12582v1 Announce Type: new Abstract: A latent recurrent language model applies a shared block of layers repeatedly, so one checkpoint can trade inference compute for accuracy by changing the loop count. At one loop…
Reflective Prompt Optimization of a Deep-Research Agent: A Topic-Disjoint, Multi-Seed Protocol for Measuring Transferable Gains and Prompt-LevelarXiv:2610.12601v1 Announce Type: new Abstract: Prompt optimization is an attractive alternative to reinforcement learning for adapting language-model agents, since it is cheap and produces human-readable artifacts. On factual…
SWE-Duel: Towards a Self-Scaling Arena for Coding AgentsarXiv:2610.12569v1 Announce Type: new Abstract: Static coding benchmarks are fixed at release. Over time their tasks leak into training data, and stronger agents eventually saturate them. We argue that a benchmark should instead…
Self-Preservation in Language ModelsarXiv:2610.12602v1 Announce Type: new Abstract: Continual learning (CL) seeks to adapt pretrained models while preserving prior capabilities. Yet the tasks supplied for preservation cover only part of what a model knows, while…
U4RASD at KnowledgeGraphEval-2026: Ontology-Constrained Encoder and LLM Systems for Arabic Relation ExtractionarXiv:2610.12742v1 Announce Type: new Abstract: This paper details our submission to KnowledgeGraphEval 2026 Subtask 2 on directed Arabic relation extraction. We explored encoder-based and large language model approaches for…
Unsupervised Multimodal Reward ModelingarXiv:2610.12707v1 Announce Type: new Abstract: Vision-language reward models are trained on annotated preference pairs, which are expensive to collect, can disagree, and are ranked by benchmark accuracy. We build one with no…
perturber: A Stateless Service for Semantics-Preserving Text PerturbationsarXiv:2610.12667v1 Announce Type: new Abstract: Large language model (LLM) evaluations on clean benchmarks overstate model robustness: real inputs arrive perturbed, and these meaning-preserving variants routinely move model…
Algebraic Integer Quantization for Machine Learning ApplicationsarXiv:2610.12494v1 Announce Type: new Abstract: In this article, we propose algebraic integer number formats (AINF) as a framework for highly configurable and accurate compressed computation. A key property of AINF is its…
An Input-Dependent Readout Phase for Resonant Sequence ModelsarXiv:2610.12496v1 Announce Type: new Abstract: Sequence models with a fixed-size state avoid the quadratic cost of attention, but face a design choice. An input-dependent state transition gives content-dependent memory at the…
An all-transistor physical-learning transformer can be trained to perform in-context learningarXiv:2610.12571v1 Announce Type: new Abstract: Most systems trained by equilibrium propagation or coupled learning are in the same class as multi-layer perceptrons: while they may be universal function approximators, they…
Behind-the-Meter Photovoltaic Visibility from Net Smart Meters: Deployment Regimes and Operational InsightsarXiv:2610.12527v1 Announce Type: new Abstract: Distribution operators need visibility of behind-the-meter photovoltaic (PV) generation, yet most residential customers are observed only through net smart meters…
CacheScope: Exact-Compute Allocation for Training-Free Diffusion AccelerationarXiv:2610.12530v1 Announce Type: new Abstract: Training-free feature reuse accelerates diffusion transformer inference by replacing full denoising computation at selected steps with cached approximations. Existing methods mainly…
CircuitTree: Composing Circuits into A Syllable TranscriberarXiv:2610.12520v1 Announce Type: new Abstract: The goal of circuit discovery is to decompose a monolithic neural network into tiny modular subnetworks which are interpretable in the sense that each does an identifiable subtask…
DiffusionART: Efficient, Stable and Scalable Reinforcement of Diffusion ModelsarXiv:2610.12572v1 Announce Type: new Abstract: Online reinforcement learning (RL) fine-tunes diffusion models with black-box rewards, but reverse-process methods such as Flow-GRPO are limited in efficiency by poor credit…
Efficient Learning of Survival Analysis Models Under Outcome-Dependent Truncation and CensoringarXiv:2610.12538v1 Announce Type: new Abstract: Modern machine learning models are typically trained on data assumed to be representative of the predictive tasks the model will face in the future, but practical datasets violate…
Enriched Holomorphic Neural Networks for 2D and 3D Laplace ProblemsarXiv:2610.12541v1 Announce Type: new Abstract: Boundary-value problems for the Laplace equation develop singular behaviour near corners, edges and junctions that smooth approximators resolve poorly. We combine holomorphic neural…
GlucoPRISM: Protocol-Supervised Pretraining for Cross-Cohort Glucose TransferarXiv:2610.12528v1 Announce Type: new Abstract: Continuous glucose monitoring (CGM) foundation models encode each day as one vector that mixes who the person is, what happened that day and how the sensor measured it, so…
Kairos: Toward a Byte-Level Foundation Model for Every ModalityarXiv:2610.12495v1 Announce Type: new Abstract: Small language models trained on a single local machine leave little room for architectural trial and error. Kairos combines bidirectional gated-DeltaNet linear attention and…
Market Impact Estimation via Causal Foundation ModelsarXiv:2610.12537v1 Announce Type: new Abstract: When a trader executes a large order, the relevant question is not \emph{what will the price be?} but \emph{what would the price have been had I not traded?} Market impact is thus a…
Realism VS Accuracy: Event Sequence Forecasting from a Generative Modeling PerspectivearXiv:2610.12586v1 Announce Type: new Abstract: Event sequences are chains of random events, each described by heterogeneous (numerical and categorical) features. The problem of event sequence forecasting occurs in finance…
Sample-Adaptive Zeroth-Order Post-TrainingarXiv:2610.12566v1 Announce Type: new Abstract: Zeroth-order (ZO) optimization offers a memory-efficient alternative to backpropagation for fine-tuning large language models. However, existing ZO methods typically sample training…
Transformer-Based Masked Diffusion Models Provably Learn Distributions with Latent StructurearXiv:2610.12544v1 Announce Type: new Abstract: Masked diffusion models (MDMs) generate discrete data by iteratively unmasking multiple tokens in parallel using a learned mask predictor. Their output carries two errors…
Silicon Valley is falling in line with Trump’s attempt to rename AIWhen President Donald Trump announced his plans to rebrand artificial intelligence as "super intelligence," you'd be forgiven for being skeptical that it would catch on. While most of the broader population is sticking with AI…
Learning to use local AI is exciting, overwhelming, and frustratingI'm embarking on a journey I've so far been hesitant to go on: actually using AI on the regular. Giving my most personal data to cloud services has been a major hold up for me, but it's increasingly possible to run powerful…
Satya Nadella says we should assume all AI models are ‘compromised’In a lengthy post on X, Microsoft's CEO laid out his views on the dangers posed by highly advanced AI models and how to confront those risks. Nadella says we can no longer accept a world where AI is treated as a "set of nested…
DistroKid has been quietly taking down songs in response to UMG lawsuitArtists are taking to social media to complain that DistroKid has unceremoniously removed their work without notice. Now DistroKid has confirmed to The Verge that the takedowns are a direct response to claims made by UMG. The…
Anthropic is cutting off its internal evaluations from the internetAfter a recent spate of high-profile incidents in which AI agents escaped containment, Anthropic is cutting off internet access for all internal evaluations. In a report Friday, the company detailed "unintended model actions,"…
Anthropic’s AI gave Philadelphia police a fake tip about an unsolved homicideAn Anthropic AI model provided false information about an unsolved homicide to a Philadelphia Police Department (PPD) tipline, according to a report from 6abc. In a statement released on Friday, the PPD said the AI model sent the…
AI agent makers are promising privacy — will they deliver?At this year's OpenAI DevDay, CEO Sam Altman unveiled the company's new AI agent Dots - and told the crowd that the company wants to "set a new standard for privacy in frontier AI." OpenAI would spend the day taking veiled shots…
‘Pure insanity’: Mathematicians will need years to make sense of OpenAI’s latest drop"Staggering." "Overwhelming." "Unprecedented." "Surreal." "Pure insanity." Those were among the descriptions more than three dozen mathematicians reached for in conversations with The Verge as they tried to make sense of the…
Nikon microscopic video competition winner disqualified for using generative AINikon says the video that originally won first place in its Small World in Motion contest "did not comply with the competition rules regarding generative AI." BBC reports that the original first place video from Dr. Ning Xu…
Trump’s attempt to rename AI is looking awfully artificialPresident Donald Trump has a knack for turning words against his enemies. His first successful presidential run was built on monikers like "Little Marco" and "Crooked Hillary"; he changed "fake news" from a phrase describing…
The Download: AI’s refusal problem and weight-loss drug side effectsThis is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology. We’re putting too much faith in AI’s ability to say no Today’s AI models are trained to…
Job titles of the future: Delivery drone air traffic controllerThe moment Trevor Wischnewsky heard that drones were delivering pizza and sushi around his Texas neighborhood, his mind was made up. “It was super fascinating,” he says. “I just immediately wanted to be a part of it.” Wischnewsky…
We’re putting too much faith in AI’s ability to say noEver since people first seriously contemplated giving machines an intelligence modeled on our own, there has never been any question that they would, like us, be able to say no. The sci-fi canon is full of stories of robotic…
We’re still figuring out the side effects of GLP-1 weight-loss drugsThis week my colleague Antonio Regalado had an interesting update on GLP-1 weight-loss drugs. According to research presented at an aging meeting in Boston, these drugs seem to affect at least some measures of biological age…
Roundtables: A Conversation With the Creator of AI-Designed VirusesFriday, October 16, 2026 Can AI design new life forms? In 2025, Stanford University PhD student Samuel King came up with a preliminary answer when he used a generative AI model to propose genetic blueprints for microscopic…
The Download: AI roadblocks for humanoids and portable rubber damsThis is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology. AI breakthroughs in robotics won’t change your life any time soon The hype around humanoid…
Why we’re watching these climate tech companiesThis week, we released our 2026 version of our Climate Tech Companies to Watch list. It’s an annual project that the MIT Technology Review team puts together. Our goal is to highlight some of the promising, interesting advances…
AI breakthroughs in robotics won’t change your life any time soonThe story is a collaboration between MIT Technology Review and Aventine, a non-profit research foundation that creates and supports content about how technology and science are changing the way we live. A robot shaped like a…
Building a safer path to autonomous industrial AIIndustrial AI is entering a new phase. After decades of predictive analytics and other specialized applications, advances in foundation models, physical AI, and agentic AI are making it possible to automate more complex tasks…
The Download: weight-loss drugs slowing aging and carbon dioxide batteriesThis is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology. Weight-loss drugs show signs of slowing biological aging, say drugmakers Popular…