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Dana-Farber Cancer Institute, Brigham and Women's Hospital, Harvard Medical School
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ACA achieves superior zero-shot classification performance in CT imaging by balancing fine-grained anatomical alignment with essential global context, all in under an hour of training.
Optimizing input configurations can boost LLM performance in pathology tasks, closing the gap with specialized models and challenging assumptions about domain-specific training.
