arXiv AI June 3, 2026 By Tong Guan, Sheng Pan, Johan Barthelemy, Zhao Li, Yujun Cai, Cesare Alippi, Ming Jin, Shirui Pan

TimeOmni-VL: Unified Models for Time Series Understanding and Generation

Read the original on arXiv AI →

arXiv:2602. 17149v2 Announce Type: replace-cross Abstract: Recent time series modeling faces a sharp divide between numerical generation and semantic understanding, with research showing that generation models often rely on superficial pattern matching, while understanding-oriented models struggle with high-fidelity numerical output.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv AI.

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