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#machine learning Preprint Sep 2026

QiYao-M: Multimodal Time Series Foundation Model with Role-Aware Modeling of Endogenous and Exogenous Modalities

The proposed QiYao-M is a role-aware multimodal TSFM that models the two types of modalities separately, including endogenous and exogenous modalities, and introduces Endo-Modality Proxy Training to train this retrieval module without exogenous multimodal pretraining data.

Han-Yin Cheng, Lin-Feng Wang, Zheng-Bo Qu et al. · 0 citations
#artificial intelligence Preprint Sep 2026

Supervision Recovery for Time Series Anomaly Detection via Context-Anchored Pairing

Experiments show that CAPS achieves the strongest aggregate performance across all four evaluation metrics among the compared methods, while complementary ablations and transfer analyses support the roles of context anchoring, semantic disentanglement, and conditional realization.

Yi-Fei Gao, Tian Lan, Yi-Meng Lu et al. · 0 citations

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