12 Aug 2025
CARES is a zero-shot, multi-agent framework designed for multi-class error detection in robotic-assisted surgery, leveraging a risk-stratified approach and clinically-informed Chain-of-Thought (CoT) prompting. The system achieved an average of 54.3 mF1 on the RARP dataset and 52.0 mF1 on the MERP dataset, outperforming baseline Vision-Language Models by up to 14% in mF1 score and remaining competitive with supervised models without requiring prior training.
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