cs.AI updates on arXiv.org 09月03日
TimeCopilot:多模型融合的预测框架
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本文介绍TimeCopilot,首个开源的预测框架,结合多种时间序列基础模型和大型语言模型,提供自动化预测流程及自然语言解释。该框架支持多种预测模型组合,在GIFT-Eval基准测试中达到最先进的概率预测性能。

arXiv:2509.00616v1 Announce Type: cross Abstract: We introduce TimeCopilot, the first open-source agentic framework for forecasting that combines multiple Time Series Foundation Models (TSFMs) with Large Language Models (LLMs) through a single unified API. TimeCopilot automates the forecasting pipeline: feature analysis, model selection, cross-validation, and forecast generation, while providing natural language explanations and supporting direct queries about the future. The framework is LLM-agnostic, compatible with both commercial and open-source models, and supports ensembles across diverse forecasting families. Results on the large-scale GIFT-Eval benchmark show that TimeCopilot achieves state-of-the-art probabilistic forecasting performance at low cost. Our framework provides a practical foundation for reproducible, explainable, and accessible agentic forecasting systems.

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时间序列模型 预测框架 多模型融合
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