STReason uses in-context learning to convert spatio-temporal queries into executable programs with specialized modules, outperforming plain LLMs on a new 150-query benchmark.
Stden: Towards physics-guided neural networks for traffic flow prediction,
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A Modular Multitask Reasoning Framework Integrating Spatio-temporal Models and LLMs
STReason uses in-context learning to convert spatio-temporal queries into executable programs with specialized modules, outperforming plain LLMs on a new 150-query benchmark.