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cs.CV2026
SIEVE: Preserving Cross-Image Evidence via Depth-Aware Token Compression
Nitish Shukla, Surgan Jandial, Nhat-Tan Bui +1
Multi-image vision-language models (VLMs) incur substantial computation when processing long visual sequences. Compressing these sequences must preserve complementary evidence acro…
cs.CV2026
CoVeR: Coverage-Based Token Pruning for Multi-View 3D Reasoning in VLMs
Nhat-Tan Bui, Varshini Elangovan, Arun Reddy Anugu +7
Representing a 3D scene as multi-view images allows 2D VLMs to reason in 3D by reusing priors from pre-training, sidestepping the scarcity of annotated 3D data. However, it produce…