Author

Hexuan Deng

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Preprint Jul 2026

Distilled Reinforcement Learning for LLM Post-training

Extensive experiments show that Distilled RL substantially outperforms standard RL and OPD in terms of both pass@1 and pass@k, and can effectively transfer previously unavailable knowledge from a teacher model to a student model.

Chen Wang, Zhaochun Li, Jionghao Bai et al. · 2 citations

Preprint Aug 2026

CRISP: Critical Step Perception for Training Efficient Deep Search Agents

This paper proposes CRISP, a framework for training efficient deep search agents through critical step perception that distinguishes interactions that gather necessary evidence from redundant ones and shapes the training reward to preserve the former while pruning the latter, improving efficiency without sacrificing the evidence needed for correct answers.

Haosi Mo, Zihao Yan, Ruiqing Zhang et al. · 0 citations