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EmoDistill is an offline framework that distills emotional negotiation skills into language model agents using Implicit Q-Learning for emotion selection and LoRA-based supervised fine-tuning and judge policy optimization for emotion expression, achieving higher utility in adversarial negotiations.
PANDO is a web agent framework that improves efficiency through online skill distillation, reducing token usage by 58-61% while outperforming baselines on VisualWebArena tasks.
A single CLAUDE.md file became GitHub's top-trending repo with 44k weekly stars by distilling Andrej Karpathy's LLM coding advice into four principles.