ACCM recovers information lost in high-rate visual token pruning by generating a question-guided caption from discarded tokens and selecting the best candidate, improving pruned LVLM accuracy with fewer FLOPs.
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Mitigating Information Loss under High Pruning Rates for Efficient Large Vision Language Models
ACCM recovers information lost in high-rate visual token pruning by generating a question-guided caption from discarded tokens and selecting the best candidate, improving pruned LVLM accuracy with fewer FLOPs.