The paper claims 92.6% dynamic visual-token pruning with retained (or 110% of) baseline VQA performance, but the full text supplied is a different paper, so the claim is unverifiable here.
MLLM s know where to look: Training-free perception of small visual details with multimodal LLM s
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A Glimpse to Compress: Dynamic Visual Token Pruning for Large Vision-Language Models
The paper claims 92.6% dynamic visual-token pruning with retained (or 110% of) baseline VQA performance, but the full text supplied is a different paper, so the claim is unverifiable here.