Vision-language models can produce fluent answers that are insufficiently grounded in the visual evidence: a single unsupported object, chart value, or intermediate inference can undermine an otherwise plausible response. We argue that this is a credit-assignment failure in multimodal post-training. Scalar outcome rewa...
Shu-Lin Tian, Ming-Lun Li, Yuhao Dong et al.· 0 citations
The Evaluation Agent framework is proposed, which employs human-like strategies for efficient, dynamic, multi-round evaluations, offering detailed, user-tailored analyses and is efficient, promptable, explainable, and scalable across models and tools.
Shu-Lin Tian, Zi-Qi Huang, Fan Zhang et al.· 2 citations
Apple-PI is introduced, the first benchmark that anchors video-model evaluation explicitly in physical laws, and is positioned as a diagnostic foundation for guiding future video models toward world models with law-grounded physical intelligence.
Runmao Yao, Kairui Hu, Yukang Cao et al.· 1 citation
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