3 papers
cs.CV2026
WorldVQA: Measuring Atomic World Knowledge in Multimodal Large Language Models
Runjie Zhou, Youbo Shao, Haoyu Lu +16
We introduce WorldVQA, a benchmark designed to evaluate the atomic visual world knowledge of Multimodal Large Language Models (MLLMs). Unlike current evaluations, which often confl…
cs.MM2025
Mitigating Audiovisual Mismatch in Visual-Guide Audio Captioning
Le Xu, Chenxing Li, Yong Ren +5
Current vision-guided audio captioning systems frequently fail to address audiovisual misalignment in real-world scenarios, such as dubbed content or off-screen sounds. To bridge t…
cs.MM2025
Hearing from Silence: Reasoning Audio Descriptions from Silent Videos via Vision-Language Model
Yong Ren, Chenxing Li, Le Xu +7
Humans can intuitively infer sounds from silent videos, but whether multimodal large language models can perform modal-mismatch reasoning without accessing target modalities remain…