7 citations · 18 across the 23 of their papers we have counts for
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cs.LG2026
TreeAdv: Tree-Structured Advantage Redistribution for Group-Based RL
Lang Cao, Hui Ruan, Yongqian Li +5
Reinforcement learning with group-based objectives, such as Group Relative Policy Optimization (GRPO), is a common framework for aligning large language models on complex reasoning…
cs.LG2025
Not All Tokens Matter: Towards Efficient LLM Reasoning via Token Significance in Reinforcement Learning
Hanbing Liu, Lang Cao, Yuanyi Ren +5
Large language models (LLMs) show strong reasoning abilities but often produce unnecessarily long explanations that reduce efficiency. Although reinforcement learning (RL) has been…
cs.LG2025
More Bang for the Buck: Process Reward Modeling with Entropy-Driven Uncertainty
Lang Cao, Renhong Chen, Yingtian Zou +9
We introduce the Entropy-Driven Uncertainty Process Reward Model (EDU-PRM), a novel entropy-driven training framework for process reward modeling that enables dynamic, uncertainty-…