2026
Tug-of-War No More: Harmonizing Accuracy and Robustness in Vision-Language Models via Stability-Aware Task Vector Merging
ICLR 2026poster
Foundation Vision-Language Models (VLMs) excel across benchmarks yet remain vulnerable to adversarial attacks. While adversarial fine-tuning improves robustness, attaining a desirable clean–robust performance trade-off typically requires costly hyperparameter searches with multiple retraining runs.…