Author

Yu Meng

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#machine learning Preprint Sep 2026

Negative Self-Distillation: Learning to Reason by Avoiding Flaws

Negative Self-Distillation (NSD) is introduced, a new framework that optimizes LLMs by diverging from flawed reasoning rather than imitating privileged solutions, and consistently outperforms OPSD and other label-free, self-bootstrapping reinforcement learning (RL) baselines.

Rong-Can Pei, Zhepei Wei, Shu-Yao Xu et al. · 1 citation

#natural language process... Dec 2025

AdaSearch: Balancing Parametric Knowledge and Search in Large Language Models via Reinforcement Learning

AdaSearch is proposed, a simple two-stage, outcome-driven RL framework that disentangles problem-solving from the decision to search, making the decision process explicit and interpretable and significantly improves search-decision quality and reduces unnecessary search calls.

Tzu-Han Lin, Wei-Lin Chen, Chen-An Li et al. · arXiv.org · 5 citations