Preprint
Aug 2026
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.
Minseok Kang, Hyunwoo J. Kim, Chanyoung Kim et al.
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