Min Tang
1 indexed paper
Recent (6 mo)
1With code
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126
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NLP×1
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2026
The Flip Side of RLHF: On-Policy Feedback for Reward Model Self-Supervised Improvement
The paper introduces SAVE, a framework that uses on-policy feedback and the value function to self-supervise and improve reward models, significantly enhancing RLHF performance across multiple benchmarks.
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Papers
cs.CLRecentMay 29, 2026
The Flip Side of RLHF: On-Policy Feedback for Reward Model Self-Supervised Improvement
Xiaobo Wang, Tong Wu, Min Tang, Jiaqi Li +2 more
The paper introduces SAVE, a framework that uses on-policy feedback and the value function to self-supervise and improve reward models, significantly enhancing RLHF performance across multiple benchma…
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