LETS-C: Leveraging Language Embedding for Time Series Classification

Recent advancements in language modeling have shown promising results when applied to time series data. In particular, fine-tuning pre-trained large language models (LLMs) for time series classification tasks has achieved state-of-the-art (SOTA) performance on standard benchmarks. However, these LLM...

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Hauptverfasser:	Kaur, Rachneet, Zeng, Zhen, Balch, Tucker, Veloso, Manuela
Format:	Artikel
Sprache:	eng
Schlagworte:	Computer Science - Artificial Intelligence Computer Science - Computation and Language Computer Science - Computational Engineering, Finance, and Science Computer Science - Learning Statistics - Methodology
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