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Deep Sight is the first framework for time series forecasting by combining fine-tuned LLMs with multi-domain agent systems. Utilizing domain-adaptive fine-tuning and agent learning, DeepSight delivers exceptional accuracy and adaptability across domains like finance, public opinion, trading, and more. This paper outlines its methodology, architecture, and applications, highlighting its capability to handle complex temporal dependencies and real-world challenges.
