3 papers
cs.LG2026
STEP: Scientific Time-Series Encoder Pretraining via Cross-Domain Distillation
Chen Zhang, Liwei Liu, Jun Tao +6
Scientific time series are central to scientific AI but are typically sparse, highly heterogeneous, and limited in scale, making unified representation learning particularly challe…
cs.CR2026
CNT: Safety-oriented Function Reuse across LLMs via Cross-Model Neuron Transfer
Yue Zhao, Yujia Gong, Ruigang Liang +4
The widespread deployment of large language models (LLMs) calls for post-hoc methods that can flexibly adapt models to evolving safety requirements. Meanwhile, the rapidly expandin…
cs.LG2026
SciTS: Scientific Time Series Understanding and Generation with LLMs
Wen Wu, Ziyang Zhang, Liwei Liu +12
The scientific reasoning ability of large language models (LLMs) has recently attracted significant attention. Time series, as a fundamental modality in scientific data, presents u…