2 papers
cs.LG2026
TimeOmni-VL: Unified Models for Time Series Understanding and Generation
Tong Guan, Sheng Pan, Johan Barthelemy +5
Recent time series modeling faces a sharp divide between numerical generation and semantic understanding, with research showing that generation models often rely on superficial pat…
cs.LG2025
ShapeX: Shapelet-Driven Post Hoc Explanations for Time Series Classification Models
Bosong Huang, Ming Jin, Yuxuan Liang +5
Explaining time series classification models is crucial, particularly in high-stakes applications such as healthcare and finance, where transparency and trust play a critical role.…