Papers by Yunyang Xuan

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Challenge:	Existing approaches to time series representation learning are time-consuming and expert-dependent, which are difficult to generalize across different tasks.
Approach:	They propose to use large language model agent to guide unsupervised time series representation learning and a framework to integrate three LLM agents to collaboratively generate positive views for time series data.
Outcome:	The proposed framework integrates large language model (LLM) agent to guide unsupervised time series representation learning and compares it with state-of-the-art baselines on multiple time series datasets.