Papers by Xuexiang Wen

1 papers
Verifier-Free RL for LLMs via Intrinsic Gradient-Norm Reward (2026.findings-acl)

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Challenge: Large Language Models (LLMs) have demonstrated remarkable capabilities in reasoning tasks and general tasks.
Approach: They propose a "Verifier-free Intrinsic Gradient-Norm Reward" that uses only the policy model itself.
Outcome: The proposed reward outperforms the state-of-the-art RLIF baseline INTUITOR on math benchmarks and shows cross-domain transfer to code benchmarks when trained only on math data.

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