AI RESEARCH
VisualOverload: Probing Visual Understanding of VLMs in Really Dense Scenes
arXiv CS.AI
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ArXi:2509.25339v3 Announce Type: replace-cross Is basic visual understanding really solved in state-of-the-art VLMs? We present VisualOverload, a slightly different visual question answering (VQA) benchmark comprising 2,720 question-answer pairs, with privately held ground-truth responses. Unlike prior VQA datasets that typically focus on near global image understanding, VisualOverload challenges models to perform simple, knowledge-free vision tasks in densely populated (or, overloaded) scenes.