arxiv
PublishedJune 2, 2026 at 4:00 AM
CLIP Tricks You: Training-free Token Pruning for Efficient Pixel Grounding in Large VIsion-Language Models
Publisher summary· verbatim
arXiv:2605.13178v2 Announce Type: replace-cross Abstract: In large vision-language models, visual tokens typically constitute the majority of input tokens, leading to substantial computational overhead. To address this, recent studies have explored pruning redundant or less informative visual tokens
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Originally published on arxiv ↗