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By incorporating language guidance into federated learning, SurgFed tackles the long-standing problem of tissue and task heterogeneity in surgical video understanding, leading to improved segmentation and depth estimation across diverse surgical settings.
A new benchmark exposes the limitations of current adversarial transferability evaluations, revealing that many reported gains may be inflated due to unfair comparisons.
