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Zi-Qing Qiao

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#artificial intelligence Preprint Sep 2026

Diffusion Reward Models

Reward models underpin the alignment of large language models, yet the dominant designs reduce each prompt--response pair to a point estimate or to a distribution from a fixed parametric family. This is at odds with human preference, which is inherently multimodal: the same response can be reasonably judged in many way...

Xiang-Yang Wang, Bing-Xiang He, Ze-Yuan Liu et al. · 0 citations
#artificial intelligence Preprint Sep 2026

StudyBench: Can Self-Evolution Squeeze Textbooks for Olympiad Capability?

StudyBench is introduced, a controlled physics benchmark that directly measures how efficiently a self-evolution method converts training material into capability, and turns self-evolution progress from an open-ended pursuit into a measurable target for future research.

Ying-Hao Chen, Zi-Xi Chen, Bingxiang He et al. · 0 citations

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