Papers by Jixiao Zhang

1 papers
GRPO-LEAD: A Difficulty-Aware Reinforcement Learning Approach for Concise Mathematical Reasoning in Language Models (2025.emnlp-main)

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Challenge: Existing methods for group-relative policy optimization face challenges in reward sparsity, verbosity and inadequate focus on problem difficulty.
Approach: They propose a method to improve group relative policy optimization with length-regularized rewards and explicit penalties for incorrect solutions.
Outcome: The proposed method achieves state-of-the-art performance for 14B-scale models . it improves reasoning accuracy, conciseness, and efficiency .

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