Unverified50% confidenceFactExact time
CARE achieves 9.0–10.8x inference speedup while providing a formal failure-risk guarantee.
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10/18/2026
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VerifiedWhen samples are severely imbalanced, Accuracy becomes misleading—a model that predicts everyone as healthy can still achieve an accuracy of over 99%.68% similarVerifiedCalibrated confidence means that when the system gives a score of 0.9, the probability of being correct should be close to 90%.68% similarUnverifiedCARE represents an evaluation paradigm shift: from the dual metrics of "average success rate + latency" to "speedup factor under a failure budget," a measure with more deployment relevance.66% similarUnverifiedFine-tuning GridSFM with just 10 scenarios can reduce cost error to below 2% and bring feasibility detection above 90%; using 1,000 scenarios can reach in-sample accuracy levels.66% similarUnverifiedThe paper reports that hybrid reasoning agents achieve accuracy about 10 percentage points higher than conventional models on multiple test sets.66% similar
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