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Large language models (LLMs) are increasingly used to discover scientific equations from experimental data. Such a discovery system has two parts that must work together: a library of executable computational tools and the model's tool-use policy. The tools supply the solving capability, from diagnosing structure in th...
These findings establish correct-solution retention as a complementary objective of recursive self-improvement (RSI) and show that generation-time intervention can improve the solution repertoire retained by subsequent students.
EmoDistill is introduced, an offline framework for distilling emotional negotiation skills from LLM-LLM interactions into smaller language-model agents and achieves competitive utility and improves over vanilla and IQL-only baselines in most settings.
VeriTrace is a cognitive-graph framework that explicitly implements three regulatory loops: interpretive update, deviation feedback, and schema revision, and achieves the strongest reproducible open-source result on DRB.
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