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cs.LG2026
Scale-Aware Pretraining of Time Series Foundation Models via Multi-Patch Token Alignment and Hybrid Masking
Taihua Chen, Xiang Ma, Yixin Zhang +3
Pretraining time series foundation models across heterogeneous datasets necessitates effective handling of varying sampling frequencies. Current methods either employ dataset-speci…
cs.LG2026
Aligning the True Semantics: Constrained Decoupling and Distribution Sampling for Cross-Modal Alignment
Xiang Ma, Lexin Fang, Litian Xu +1
Cross-modal alignment is a crucial task in multimodal learning aimed at achieving semantic consistency between vision and language. This requires that image-text pairs exhibit simi…