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A single benchmark now enables city-scale, multimodal OD flow forecasting across six modes and sub-district granularity, revealing that scaling spatio-temporal models and naive joint training often fail.
The 1-block STGCN variant achieves superior performance with significantly lower computational costs, challenging the assumption that deeper architectures are always better for traffic prediction.
