Author

Zhen-Chen Tang

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Preprint Sep 2026

Think Before You Score: Thinking Reward Model for Visual Generation

Visual reward models are essential for evaluating and improving visual generation models, yet existing approaches typically map task conditions and candidate outputs directly to scalar rewards, leaving implicit what should be evaluated for each individual case. We introduce Think Before You Score, a paradigm that expli...

Xue-Yuan Bai, Zhen-Chen Tang, Yang Shi et al. · 0 citations

#artificial intelligence Preprint Sep 2026

RewardVerse: Rubric-Guided Policy Optimization for Video Reward Modeling

RewardVerse, a rubric-based video reward framework that introduces a dynamic rubric as an intermediate representation between the evaluation query and the scorer, mitigates scalar drift, and provides a robust and interpretable reward signal for RL in video generation.

Zhen-Chen Tang, Yang Li, Songlin Yang et al. · 1 citation

#artificial intelligence Preprint Sep 2026

An Evolutionary Agentic Approach for Open-ended Image Quality Perception

Generative models are rapidly expanding image quality assessment (IQA) beyond traditional fidelity factors to emerging dimensions such as physical plausibility and text-rendering correctness. However, existing IQA models rely on fixed definitions and heavy supervision, making them difficult to extend to open-ended perc...

Zhenchen Tang, Bo Peng, Zi-Chuan Wang et al. · 1 citation