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Author

Biao Liu

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Preprint Aug 2026

TrustRoboReward: Preference-Ordered Isotonic Score Editing for Multi-Paradigm Robot Reward Models

This work proposes TrustRoboReward, a multi-paradigm reward modeling framework equipped with Preference-Ordered Isotonic Score Editing (POISE), and constructs a unified four-paradigm dataset with trajectory progress scoring, video-QA answer quality scoring, and their pairwise counterparts.

Yi-Dong Wang, Yan Zhan, Ziteng Feng et al. · 0 citations
Aug 2026

Debiased label enhancement for class-imbalanced semi-supervised learning

A novel semi-supervised framework that disentangles pseudo-label generation from the classification task via designing a dedicated pseudo-label generator to align the class distributions between labeled and unlabeled data is proposed.

Yifan Wang, Biao Liu, Xin Geng et al. · 0 citations

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