DiffPrune: differentiable information throttling for token pruning in vision-language models
DiffPrune is proposed, which gives token scores a direct meaning and implements an Information Throttler, which injects variance-preserving noise into visual tokens, where high-score tokens remain close to their original representations, while low-score tokens carry less original information.