Did We Actually Fix It? An Independent Adversarial Stress-Test of Post-Point-Adjustment Evaluation Metrics for Time-Series Anomaly Detection

arXiv 2607.11969•0d9eb8e41b719853fae1a0858a8c9c3614c0342ed41c36d7dee5899ba4a630bc
adversarial-testinganomaly-evasionbenchmarkingevaluation-metricsmachine-learningmetric-selectionmonitoringopen-sourcepip-packageresearchrobust-evaluationtime-series-anomaly-detection

Paper metadata

arXiv ID
2607.11969
Version
Not specified by this published record
Category
Statistics — Machine Learning (stat.ML)

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Evidence and limitations

Source ID
arxiv_stat_ml
Record identifier
0d9eb8e41b719853fae1a0858a8c9c3614c0342ed41c36d7dee5899ba4a630bc
Enrichment time
2026-07-15T07:23:54Z
AI-assisted enrichment
Yes

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Did We Actually Fix It? An Independent Adversarial Stress-Test of Post-Point-Adjustment Evaluation Metrics for Time-Series Anomaly Detection · Baitaphish