Tech
No Channels Left Behind: Understanding Diffusion Acceleration through Residual Gates
arXiv:2610.40914v1 Announce Type: new Abstract: Training acceleration methods for diffusion transformers, such as REPA and dispersive regularization, are commonly explained by additional supervision, spatial-structure priors, or…
- Published
- (1 h ago)
- Outlet
- arXiv cs.LG
- Section
- Tech
- Length here
- Headline and 26-word snippet. The full article is at the source.
More from arXiv cs.LG and around the same time
A Theoretical Framework for Understanding and Building "Any-task inference" Capable Foundation ModelsarXiv:2610.40934v1 Announce Type: new Abstract: In this work, we provide a formal framework and mathematical definition for the subset of foundation models focused on enabling the property of "any-task inference" (ATI) (similar…
AutoHebb: Self-Modifying Neural Networks that Zero-Shot Infer and Continually LearnarXiv:2610.40757v1 Announce Type: new Abstract: Humans and animals have a unique capacity to generalize and learn in novel circumstances, including "0-shot" inference (ZI) and continual learning (CL) -- two powerful cognitive…
Automatic Construction of Strong Simple BaselinesarXiv:2610.40700v1 Announce Type: new Abstract: To rigorously establish the value of a novel deep learning method, it must be compared against appropriate baselines. As deep learning has become increasingly common in the physical…
Bayesian Distribution System State Estimation with Flow MatchingarXiv:2610.40728v1 Announce Type: new Abstract: Medium-voltage feeders have few real-time measurements, so distribution system state estimation (DSSE) rests on pseudo-measurements of the secondary substations, a prior in Bayesian…
Certified Behavioral Retention for Continual Adaptation with Held-Out AnchorsarXiv:2610.40740v1 Announce Type: new Abstract: Continual adaptation requires deciding not only how to update a model, but whether to commit an update without exceeding a declared budget for changes to protected behavior. We…
Don't Just Impute, Detect: Task-Aware Diffusion Pipelines for Edge Anomaly DetectionarXiv:2610.40732v1 Announce Type: new Abstract: Industrial Internet of Things (IIoT) edge pipelines routinely lose contiguous blocks of multi-sensor data to network dropouts and hardware faults. The standard remedy is a…This page holds the headline and a short snippet as published by arXiv cs.LG, 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.
