Unverified50% confidenceBenchmarkExact time
In experiments on the Loghub HDFS_v1 dataset, Decision-1 initially used a simple prompt and reached only 49% accuracy (AUC 0.68), lower than the 71% rule-based baseline.
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Long-term
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10/13/2026
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UnverifiedWhen labeled data and a stable schema are available, a logistic regression classifier reached 95.1% accuracy with 50 labeled blocks and 99.7% with 8000 blocks on the HDFS anomaly detection task, surpassing the 86% of the zero-shot LLM.76% similarUnverifiedIn HDFS anomaly detection, Decision-1's raw output probabilities correlate 0.43 with event count and only 0.14 with labels; the model overreacts to lexical cues and log volume, and misjudges missing events as healthy.69% similarUnverifiedOn the RCAEval RE2-OB microservice root cause localization dataset, Decision-1 correctly identified the root cause service 85 times out of 90 cases, with 94% accuracy, exceeding the 82% of the 'maximum metric deviation' rule-based baseline (McNemar p=0.013).68% similarUnverifiedFor the 7B model, accuracy with the solver was 75.31% versus 72.02% for direct calculation, a paired improvement of +3.29 percentage points, with a 95% cluster interval of [-3.49, 10.38] crossing zero, making the advantage non-significant.65% similar
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