Are We Evaluating VLM Token Pruning Right? Looking Beyond Accuracy and Token Count.

arXiv:2610.24740v1 Announce Type: new Abstract: Visual token pruning aims to reduce inference cost while preserving the capabilities of the original VLM. Yet existing evaluations rely on aggregate task accuracy and retained token count as proxies for pruning q