Papers by Qianrun Wei

1 papers
CROP: Contextual Region-Oriented Visual Token Pruning (2025.emnlp-main)

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Challenge: Existing VLMs process entire images, leading to excessive visual tokens . redundant image information also introduces a large number of visual token, requiring much higher memory and computation in VLM.
Approach: They propose a framework to prune visual tokens using localization and pruning . they propose CROP to locate local image regions relevant to the query .
Outcome: The proposed framework outperforms existing visual token pruning methods on a wide range of tasks.

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