arXiv AI July 7, 2026 By Pierre Lotte (EPE UT, IRIT), Andr\'e P\'eninou (UT2J, IRIT-SIG, IRIT), Olivier Teste (IRIT-SIG, IRIT, UT2J, Comue de Toulouse)

Fun-TSG: A Function-Driven Multivariate Time Series Generator with Variable-Level Anomaly Labeling

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arXiv:2604. 14221v2 Announce Type: replace Abstract: Reliable evaluation of anomaly detection methods in multivariate time series remains an open challenge, largely due to the limitations of existing benchmark datasets.

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efficiency benchmarks safety

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By Jinju Park, Seokho Kang

llms rag benchmarks

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CAST: Context- and Anomaly Structure-Conditioned Time Series Anomaly Generation

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Anomaly Detection for Sparse and Irregular Multivariate Time Series with Latent SDEs

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