arXiv Machine Learning June 9, 2026 By Jiashun Liu, Runze Liu, Xu Wan, Jing Liang, Hongyao Tang, Ling Pan

Reformulate LLM Reinforcement Learning for Efficient Training under Black-box Discrepancy

Read the original on arXiv Machine Learning →

arXiv:2606. 08779v1 Announce Type: new Abstract: Reinforcement Learning (RL) has emerged as a pivotal post-training paradigm, yet it frequently suffers from unpredictable sub-optimum performance or even training collapses.

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