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cs.CV2026
Fine-Grained Multi Image Object Hallucination Benchmark
Joonki Min, Chaeyun Kim, Hyungwook Choi +4
Multimodal Large Language Models (MLLMs) are increasingly deployed in multi-image scenarios requiring complex reasoning across visual contexts. However, current MLLMs remain fundam…
cs.CV2026
Can MLLMs Reason About Visual Persuasion? Evaluating the Efficacy and Faithfulness of Reasoning
Naeun Lee, Hyunjong Kim, Sunghwan Choi +2
Persuasive visuals play a central role in advertising, public communication, and online media, making it increasingly important to understand whether an image is persuasive and why…
cs.CV2026
Towards Motion-aware Referring Image Segmentation
Chaeyun Kim, Seunghoon Yi, Yejin Kim +2
Referring Image Segmentation (RIS) requires identifying objects from images based on textual descriptions. We observe that existing methods significantly underperform on motion-rel…