Tracked topic
… Existing failure detection methods either rely on expensive action resampling or external models, while alternatives propagate trajectory-level labels uniformly across every timestep, obscuring localized failure signals. …
Papers arxiv:2605.29588 Brain-IT-VQA: From Brain Signals to Answers Published on May 28 Submitted by Roman Beliy on Jun 2 Weizmann Institute of Science Authors: , , , , Abstract Brain-IT-VQA framework decodes visual content from fMRI signals using transformer-based architecture and introduces NSD-V… …
… While latent memory offers a solution to compress interaction histories, its training lacks reliable supervisory signals. …
… ClawHub Security Signals is designed to expose that boundary. …
… Therefore, we propose reading the original self-distillation signal in reverse: when the student succeeds along a path the teacher would not have predicted, these tokens reflect its self-driven reasoning. …
… Ablations show that the three axes provide complementary supervision signals, while the reward preserves overall video generation quality with only modest training overhead. …
… Which teacher model should be used, and in the case of self-distillation , which specific context should serve as the supervisory signal? …
Papers arxiv:2604.28075 Repetition over Diversity: High-Signal Data Filtering for Sample-Efficient German Language Modeling Published on Apr 30 Submitted by Stefan Schweter on May 5 Boldt Authors: Ansar Aynetdinov , Patrick Haller , Abstract Training high-quality filtered data multiple times yields… …
… AI-generated summary Model internals encode rich information about how a large language model LLM processes its training data; however, post-training data engineering largely relies on external signals and ignores rich intrinsic signals lying in model internals. …
… DataCOPE derives verifier signals from the exploration trajectories and uses them to characterize relative quality or aggreement among trajectories. …