Unverified50% confidenceBenchmarkExact time
Random forest classifiers generally exceed 90% accuracy on the KOI dataset after hyperparameter tuning.
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9/21/2026
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UnverifiedExperimental data shows that when key information is located at the beginning and end of the input sequence, the model's retrieval accuracy can be as high as over 90%, but when located in the middle, it may drop sharply to below 60%.64% similarUnverifiedOn the MNIST dataset, even a simple linear classifier can achieve approximately 92% accuracy.63% similarUnverifiedOn the CLINC150 benchmark, 80 fine-tuning samples can bring vector routing to an accuracy of 85.9%, while a full fine-tune can exceed 96%.63% similarUnverifiedOn reasoning-based question-answering tasks, the strongest closed-source models achieved accuracy exceeding 90%.62% similar
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