Many recent multivariate time series anomaly detection (MTSAD) models incorporate cross-channel modeling, under the implicit assumption that the structure of anomalies may be spread across multiple channels. We evaluate this assumption on eight widely used public benchmarks by introducing a per-segment diagnostic framework that flags, for each labeled anomaly, whether at least one channel deviates individually from its normal history, whether the cross-channel correlation structure changes, or both. The framework shows that no cross-channel rupture occurs without an accompanying univariate deviation across a range of reasonable thresholds. A complementary metric also reveals that on six of the eight benchmarks, at least half of the labeled anomaly segments deviate univariately on 89% to 100% of their timesteps, reaching 100% on three of these datasets. To verify that our framework captures cross-channel structure when present, we construct synthetic data of phase-shifted sinusoidal channels with shared noise. Each anomalous segment is altered through one of two channel-wise corruptions that preserve the per-channel marginal distribution while breaking cross-channel structure, and our framework correctly characterizes these segments as cross-channel-only. On these data, channel-dependent (CD) models successfully exploit the cross-channel signal whereas channel-independent (CI) ones fail. The CI/CD comparison of a recent SOTA detector on real benchmarks further confirms that CD modeling brings no measurable gain. We conclude that current MTSAD benchmarks are unsuitable for validating cross-channel modeling capabilities, and we call for the development of more structurally diverse evaluation sets. The code for this study is publicly available.

翻译：近年来，许多多变量时间序列异常检测（MTSAD）模型融入了跨通道建模，其隐含假设是异常结构可能分布在多个通道上。通过引入一个逐段诊断框架，我们在八个广泛使用的公开基准上评估了这一假设。该框架针对每个标注的异常段，标记是否存在至少一个通道相对于其正常历史出现单独偏离、跨通道相关结构发生变化，或两者兼有。该框架表明，在一系列合理阈值下，没有跨通道断裂是在没有伴随的单变量偏离的情况下发生的。一项补充指标进一步揭示，在八个基准中的六个中，至少一半的标注异常段在89%至100%的时间步上呈现单变量偏离，其中三个数据集达到100%。为了验证我们的框架能在存在跨通道结构时正确捕获它，我们构建了由相位偏移正弦波通道和共享噪声组成的合成数据。每个异常段通过两种通道级破坏之一进行修改，这些破坏保留了每个通道的边缘分布，同时打破了跨通道结构，而我们的框架将这些段正确表征为仅跨通道异常。在这些数据上，通道依赖（CD）模型成功利用了跨通道信号，而通道独立（CI）模型则失败。在真实基准上对最近SOTA检测器的CI/CD比较进一步证实，CD建模并未带来可衡量的增益。我们得出结论，当前的MTSAD基准不适合验证跨通道建模能力，并呼吁开发结构更多样化的评估集。本研究的代码已公开。