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cs.CV2026
EvoCut: Multi-Layer Evolution-Aware Visual Token Compression for Efficient Large Vision-Language Models
Hongyu Lu, Feng Zhang, Wenwei Jin +5
Large vision-language models (LVLMs) achieve strong performance on image and video understanding tasks, but their inference efficiency is constrained by the large number of visual…
cs.CV2026
LRCP: Low-Rank Compressibility Guided Visual Token Pruning for Efficient LVLMs
Hongyu Lu, Feng Zhang, Wenwei Jin +5
Large vision-language models (LVLMs) achieve strong multimodal understanding, but their inference cost grows rapidly with the number of visual tokens, especially for high-resolutio…
cs.LG2026
Sparsity and Out-of-Distribution Generalization
Scott Aaronson, Lin Lin Lee, Jiawei Li
Explaining out-of-distribution generalization has been a central problem in epistemology since Goodman's "grue" puzzle in 1946. Today it's a central problem in machine learning, in…