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This paper introduces a joint latent clustering approach for anomaly detection in multimodal cyber-physical systems, modeling normal behavior as a mixture of Gaussians in latent space, and proposes a fair evaluation protocol. It achieves state-of-the-art results on three real-world CPS datasets, particularly on difficult subsets.