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cs.LG2026
rePIRL: Learn PRM with Inverse RL for LLM Reasoning
Xian Wu, Kaijie Zhu, Ying Zhang +2
Process rewards have been widely used in deep reinforcement learning to improve training efficiency, reduce variance, and prevent reward hacking. In LLM reasoning, existing works a…
cs.LG2024★ 1 cited
Revisit Micro-batch Clipping: Adaptive Data Pruning via Gradient Manipulation
Lun Wang
Micro-batch clipping, a gradient clipping method, has recently shown potential in enhancing auto-speech recognition (ASR) model performance. However, the underlying mechanism behin…