blacksnail789521/Time-Series-Reasoning-Survey

A Survey of Reasoning and Agentic Systems in Time Series with Large Language Models

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This is a comprehensive overview for researchers and practitioners interested in using large language models (LLMs) for time series analysis. It compiles and categorizes existing research papers and non-research contributions, providing a structured way to understand how LLMs are applied to tasks like forecasting, classification, and anomaly detection. If you are a researcher or data scientist exploring LLM applications in time series, this survey helps you navigate the current landscape and identify relevant work.

Use this if you are a researcher or data scientist looking for a structured overview of how large language models (LLMs) are being used for time series problems like forecasting, anomaly detection, or explanation.

Not ideal if you are looking for an off-the-shelf software tool or code library to directly apply LLMs to your time series data.

time-series-analysis forecasting large-language-models anomaly-detection causal-inference
No Package No Dependents
Maintenance 6 / 25
Adoption 7 / 25
Maturity 15 / 25
Community 3 / 25

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MIT

Last pushed

Oct 29, 2025

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