AI RESEARCH

Towards Faithful Reasoning in Comics for Small MLLMs

arXiv CS.CV

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.