AI RESEARCH
Hint-Guided Diversified Policy Optimization for LLM Reasoning
arXiv CS.CL
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ArXi:2606.03021v1 Announce Type: new Recent developments in Large Language Models (LLMs) have showcased impressive reasoning capabilities, with Reinforcement Learning with Verifiable Rewards (RLVR) being a promising enhancement strategy. However, existing reward mechanisms are constrained to the outcome-level correctness and lack explicit signals to guide the model to consider diverse solutions.