Papers by Haomin Wen

1 papers
Embracing Large Language Models in Traffic Flow Forecasting (2025.findings-acl)

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Challenge: Existing methods to predict future traffic flows capture spatio-temporal dependencies, but they fail to adapt to test-time environmental changes.
Approach: They propose to use large language models to help traffic flow forecasting by capturing spatio-temporal dependencies and using a large language model to select the most likely result.
Outcome: The proposed method is based on large language models (LLMs) and an LLM-based selector.

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