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cs.CV2026
When Vision Speaks for Sound
Xiaofei Wen, Wenjie Jacky Mo, Xingyu Fu +6
Despite rapid progress in video-capable MLLMs, we find that their apparent audio understanding in videos is often vision-driven: models rely on visual cues to infer or hallucinate…
cs.CV2026
CARPE: Context-Aware Image Representation Prioritization via Ensemble for Large Vision-Language Models
Donghee Lee, Rui Cai, Zhe Zhao
Large vision-language models (LVLMs) are typically trained using autoregressive language modeling objectives, which align visual representations with linguistic space. While effect…