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
This work delineates LLM reasoning boundaries and presents a new paradigm for fine-grained capability assessment, which suggests that genuine reasoning is demonstrated only when a model follows logical rules despite conflicting prior knowledge.
Fangfei Yan, Jianbo Yao, Michael K. Chen et al.· Proceedings of the 32nd ACM...· 1 citation
This work delineates LLM reasoning boundaries and presents a new paradigm for fine-grained capability assessment, which suggests that genuine reasoning is demonstrated only when a model follows logical rules despite conflicting prior knowledge.
Fangfei Yan, Jianbo Yao, Michael K. Chen et al.· Proceedings of the 32nd ACM...· 1 citation
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