AI RESEARCH
Towards Faithful Reasoning in Comics for Small MLLMs
arXiv CS.CV
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ArXi:2601.02991v2 Announce Type: replace Comic understanding presents a significant challenge for Multimodal Large Language Models (MLLMs), as the intended meaning of a comic often emerges from the joint interpretation of visual, textual, and social cues. This naturally motivates Chain-of-Thought (CoT) prompting, since explicit intermediate reasoning appears promising for integrating such heterogeneous signals.