Diversity-Aware Policy Optimization for Large Language Model Reasoning

This work studies the relationship between solution diversity and reasoning potential in LLM reasoning, and proposes a diversity-aware policy optimization method for reinforcement learning training.

Recommended citation: Yao, J., Cheng, R., Wu, X., et al. (2025). "Diversity-Aware Policy Optimization for Large Language Model Reasoning." NeurIPS 2025 Spotlight.
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