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cs.CV2026
Validating, Not Sampling: Region-Level Robustness of Vision-Language and Vision-Language-Action Models
Bogdan Aron, Christopher Brix, Benedikt Brückner +3
Vision-language models (VLMs) and vision-language-action models (VLAs) are increasingly deployed in real-world applications. There, a small perturbation to the recorded camera imag…
cs.CV2024
Towards Fairness-Aware Adversarial Learning
Yanghao Zhang, Tianle Zhang, Ronghui Mu +2
Although adversarial training (AT) has proven effective in enhancing the model's robustness, the recently revealed issue of fairness in robustness has not been well addressed, i.e.…