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cs.LG2026
Two-Fidelity Best-Action Identification for Stochastic Minimax Tree
Peter Chen, Xi Chen
We study fixed-confidence best-action identification (BAI) in stochastic minimax trees. This problem is increasingly relevant in modern AI planning, where deep minimax search and M…
cs.LG2026
Stepwise Guided Policy Optimization: Coloring your Incorrect Reasoning in GRPO
Peter Chen, Xiaopeng Li, Ziniu Li +2
Reinforcement learning (RL) has proven effective in strengthening the reasoning capabilities of large language models (LLMs). A widely adopted method, Group Relative Policy Optimiz…
cs.LG2026
Exploration vs Exploitation: Rethinking RLVR through Clipping, Entropy, and Spurious Reward
Peter Chen, Xiaopeng Li, Ziniu Li +3
This paper examines the exploration-exploitation trade-off in reinforcement learning with verifiable rewards (RLVR), a framework for improving the reasoning of Large Language Model…