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Composition, Not Conversation: VLMs Lose the Scene, Not the Thread

Vision-language models (VLMs) increasingly reason over visual evidence that is cropped, segmented, retrieved, or revealed over time. Yet most VQA benchmarks present the complete image and question at once. We ask what models lose when the same information is fragmented.

By L. D. M. S. Sai Teja, Ufaq Khan, N. Siva Gopala Krishna, Satyajit Tourani, Ashshak Sharifdeen, Fida Mohammad Thoker, Bernard Ghanem, Muhammad Haris KhanarXiv - cs.CV (CV)

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Originally published by arXiv - cs.CV (CV) on Oct 1, 2026.

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