Author

Cheng-Hao Liu

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Preprint Oct 2026

TimesJev: Thinking Fast on Time Series with System 1 Sufficiency

Large language models (LLMs) have recently shown strong potential for time series reasoning, while models that reason over time series are usually with long chains of thought. However, this process often consumes thousands of tokens, directly leading to substantial latency during inference. In contrast, System 1 models...

Cheng-Hao Liu, Wei Fan, Jin-Dong Han et al. · 0 citations

#artificial intelligence Jul 2026

Post-Training in Time Series Foundation Models: A Unifying Framework

This work analyzes TSFM post-training methods based on their locus of intervention in the prediction pipeline, yielding five categories: parameter adaptation, context augmentation, model composition, output processing and uncertainty control, and compression and specialization.

Shi-Feng Xie, Ambroise Odonnat, Ze-Hao Xiao et al. · arXiv.org · 3 citations