Nexus framework uses multi-agent approach for time series forecasting

Researchers have introduced Nexus, a novel multi-agent framework designed to enhance time series forecasting by integrating unstructured contextual data with numerical patterns. This framework decomposes the forecasting process into distinct stages, allowing for the isolation of macro and micro-level temporal fluctuations and the incorporation of real-world textual signals. Evaluations on financial and real estate data, extending beyond LLM knowledge cutoffs, demonstrate that Nexus matches or surpasses state-of-the-art models and provides transparent reasoning traces for its predictions. AI

影响 Introduces a new agentic reasoning approach to time series forecasting, potentially improving accuracy and interpretability for complex real-world data.

排序理由 Publication of an academic paper detailing a new framework for time series forecasting. [lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.CL 阅读 →

• Nexus
• Sarkar Snigdha Sarathi Das

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