Tech
DS@GT ARC at CheckThat! 2026: A Verdict-Anchored Pipeline for Generating Fact-Checking Articles
arXiv:2611.05382v1 Announce Type: new Abstract: Misinformation spreads faster than professional fact-checkers can manually verify it and write articles explaining their verdicts. This creates a need to automate the production of…
- Published
- (4 min ago)
- Outlet
- arXiv cs.CL
- Section
- Tech
- Length here
- Headline and 30-word snippet. The full article is at the source.
More from arXiv cs.CL and around the same time
AI-Driven SaaS Platform Integration: AI Express for Unified Generative AI Services with Pay-As-You-Go Credit Systems and Scalable MicroservicearXiv:2611.05389v1 Announce Type: new Abstract: Generative AI is currently fragmented, with separate subscriptions required for text generation, image synthesis, and code assistance, leading to high costs and workflow…CCDWIKI: Decoupling Case Formulation from Response Generation in Longitudinal CBT DialoguearXiv:2611.05383v1 Announce Type: new Abstract: Cognitive Behavioral Therapy (CBT) demands more than empathic validation, requiring instead a structured formulation of the interplay among situations, automatic thoughts, emotions…Cognitive Bias Signatures in Search-Equipped LLM Agents: A Stage-Resolved AnalysisarXiv:2611.05720v1 Announce Type: new Abstract: Search can help LLM agents correct mistakes, but their starting conditions may shape which evidence they find and use. Drawing on cognitive-bias paradigms, we develop a controlled…Contextual Pictograms for Repairing Multilingual ASR ErrorsarXiv:2611.05637v1 Announce Type: new Abstract: Speech transcription errors can be difficult to recognize when competing word hypotheses are unfamiliar or visually similar. We describe an interface that combines alternative…Discourse Analysis of Legislative Bill DiscussionsarXiv:2611.05381v1 Announce Type: new Abstract: Legislative hearings are distinct communication events with their own human recognizable structure and logic, yet they have been analyzed as distinct phenomena beyond their…How Well Can Large Language Models Impersonate Individual Authors? A Comparative EvaluationarXiv:2611.05771v1 Announce Type: new Abstract: This study investigates the authorship impersonation capacity of six widely used large language models (LLMs): Gemini 3 Pro, Claude Opus, GPT 5.2, GPT 5.2 Pro, DeepSeek 3.2, and…This page holds the headline and a short snippet as published by arXiv cs.CL, whose feed they came from. The story itself, the photography and the rights stay with them, and the button above goes straight to their site. We keep this page so the headline has a stable address and a record of when it ran.
