Hyunwoo J. Kim

Prune Once: Retraining-Free Task-Agnostic Pruning for Vision-Language Models

A retraining-free VLM pruning framework called PORTA is introduced that derives a task- and modality-agnostic importance formulation based on activation variation, estimated from generic calibration data, which reliably captures feature-level representation utility across modalities.