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Corresponding author are Bo Cheng and Soujanya Poria
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By explicitly grounding reasoning steps to visual objects, Chain-of-Glimpse enables more accurate and interpretable video understanding, outperforming object-agnostic methods on multiple benchmarks.
Current VLMs can ace image quizzes, but completely fumble when asked to stack blocks in a physically plausible way, revealing a critical gap in understanding real-world physics.
