Papers by Chenqing Liu

1 papers
HEALing Entropy Collapse: Enhancing Exploration in Few-Shot RLVR via Hybrid-Domain Entropy Dynamics Alignment (2026.acl-long)

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Challenge: Existing methods for training reasoning-oriented large language models assume high-resource settings with abundant data.
Approach: They propose a framework that integrates high-value general-domain data to promote more diverse exploration.
Outcome: The proposed framework matches or surpasses RLVR trained with 32 target-domain samples using 32 target domain samples.

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