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Who Speaks for the Pruned? Visual Token Pruning as Coverage Optimization

This story is from 2026-09-04. It is preserved in the archive; the latest stories are on the live feed.

arXiv:2609.03158v1 Announce Type: new Abstract: Visual token pruning reduces the inference cost of vision-language models (VLMs), but most methods only ask which tokens to keep. This retained-token view can keep redundant high-scoring tokens while leaving discarded evidence without a close represen…

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  1. 2026-09-04 04:00 · arXiv cs.CV
    Who Speaks for the Pruned? Visual Token Pruning as Coverage Optimization

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