Unverified50% confidenceBenchmarkExact time
Fine-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.
1
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50%
Confidence
Medium-term (~90 days)
Relevance
10/1/2026
First Seen
Valid until: 12/30/2026
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UnverifiedThe accuracy data in the test has an error margin of approximately ±8–10 percentage points at n=100 sample size (based on a 95% confidence-level binomial confidence interval).73% similarUnverified参数量在1亿以下的轻量模型经领域数据微调后可达95%以上意图分类准确率，单次推理延迟控制在5-20ms以内71% similarUnverifiedCalibrated confidence means that when the system gives a score of 0.9, the probability of being correct should be close to 90%.71% similarUnverifiedIn a fraud detection task with a positive-to-negative sample ratio of 1:99, a model that predicts all samples as 'non-fraud' can still achieve 99% accuracy.71% similarUnverifiedOn simple visual perception tasks, ordinary humans can achieve over 90% accuracy, while most SOTA models achieve only 50% or even lower.70% similar
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