Unverified50% confidenceBenchmarkExact time
With 10^6 training samples, ΦasmaNet achieves 100-MAPE=98.73% on the held-out test set.
1
Sources
50%
Confidence
Medium-term (~90 days)
Relevance
11/4/2026
First Seen
Valid until: 2/2/2027
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Related Claims
VerifiedIn the same reproduction experiment, ResNet-20 achieved a test accuracy of 90.4% and ResNet-56 achieved a test accuracy of 91.7%, with training accuracies of 97.4% and 99.0% respectively.79% similarUnverifiedThe handwritten MLP model can achieve approximately 98.5% accuracy on the full MNIST training set.72% similarVerifiedIn a reproduction experiment training for 40 epochs on CIFAR-10, plain-56 achieved a training accuracy of 84.0% and plain-20 achieved a training accuracy of 95.1%, even though plain-56's parameter count (853,018) is approximately three times that of plain-20 (269,722).70% similarUnverifiedThe 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).69% similarUnverifiedTools scoring below 40 were correctly selected 95.5% of the time, while tools scoring 60 to 79 instead reached 100%.69% similar
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