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 explicitly determines what matters for each case before judging h
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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 explicitly determines what matters for each case before judging h
This research introduces a novel approach to reward modeling for visual generation, moving beyond scalar rewards to case-adaptive rubrics and fine-grained assessment. For ML engineers, understanding this paradigm shift is crucial for developing more robust and interpretable visual generation systems, especially in areas requiring nuanced evaluation.