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cs.CL2025
DuaShepherd: Integrating Stepwise Correctness and Potential Rewards for Mathematical Reasoning
Yuanhao Wu, Juntong Song, Hanning Zhang +2
In this paper, we propose DuaShepherd, a novel reward modeling framework that integrates two complementary reward signals, correctness and potential, to enhance the mathematical re…
cs.CL2025★ 3 cited
OpenGenAlign: A Preference Dataset and Benchmark for Trustworthy Reward Modeling in Open-Ended, Long-Context Generation
Hanning Zhang, Juntong Song, Juno Zhu +3
Reward Modeling is critical in evaluating and improving the generation of Large Language Models (LLMs). While numerous recent works have shown its feasibility in improving safety,…