% Key papers for Spatio-temporal graph traffic forecasting (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{aaai2019_attention_100173,
  title = {{Attention Based Spatial-Temporal Graph Convolutional Networks for Traffic Flow Forecasting}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2019},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/3881},
}

@inproceedings{aaai2017_deep_105693,
  title = {{Deep Spatio-Temporal Residual Networks for Citywide Crowd Flows Prediction}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2017},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/10735},
}

@inproceedings{aaai2020_gman_100304,
  title = {{GMAN: A Graph Multi-Attention Network for Traffic Prediction}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2020},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/5477},
}

@inproceedings{aaai2020_spatial_100265,
  title = {{Spatial-Temporal Synchronous Graph Convolutional Networks: A New Framework for Spatial-Temporal Network Data Forecasting}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2020},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/5438},
}

@inproceedings{cvpr2020_social_16260,
  title = {{Social-STGCNN: A Social Spatio-Temporal Graph Convolutional Neural Network for Human Trajectory Prediction}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2020},
}

@inproceedings{aaai2021_spatial_1407,
  title = {{Spatial-Temporal Fusion Graph Neural Networks for Traffic Flow Forecasting}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2021},
  url = {https://aaai.org/papers/04189-spatial-temporal-fusion-graph-neural-networks-for-traffic-flow-forecasting/},
}

@inproceedings{aaai2019_spatiotemporal_101555,
  title = {{Spatiotemporal Multi-Graph Convolution Network for Ride-Hailing Demand Forecasting}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2019},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/4247},
}

@inproceedings{aaai2019_revisiting_101796,
  title = {{Revisiting Spatial-Temporal Similarity: A Deep Learning Framework for Traffic Prediction}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2019},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/4511},
}

@inproceedings{aaai2023_pdformer_4328,
  title = {{PDFormer: Propagation Delay-Aware Dynamic Long-Range Transformer for Traffic Flow Prediction}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2023},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/25556},
}

@inproceedings{aaai2018_when_105768,
  title = {{When Will You Arrive? Estimating Travel Time Based on Deep Neural Networks}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2018},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/11877},
}

@inproceedings{aaai2022_graph_2167,
  title = {{Graph Neural Controlled Differential Equations for Traffic Forecasting}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2022},
  url = {https://aaai.org/papers/06367-graph-neural-controlled-differential-equations-for-traffic-forecasting/},
}

@inproceedings{aaai2019_dynamic_100169,
  title = {{Dynamic Spatial-Temporal Graph Convolutional Neural Networks for Traffic Forecasting}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2019},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/3877},
}

@inproceedings{aaai2020_multi_101898,
  title = {{Multi-Range Attentive Bicomponent Graph Convolutional Network for Traffic Forecasting}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2020},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/5758},
}

@inproceedings{aaai2019_deepstn_100184,
  title = {{DeepSTN+: Context-Aware Spatial-Temporal Neural Network for Crowd Flow Prediction in Metropolis}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2019},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/3892},
}

@inproceedings{aaai2020_spatio_100297,
  title = {{Spatio-Temporal Graph Structure Learning for Traffic Forecasting}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2020},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/5470},
}

@inproceedings{aaai2019_gated_99935,
  title = {{Gated Residual Recurrent Graph Neural Networks for Traffic Prediction}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2019},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/3821},
}

@inproceedings{aaai2021_hierarchical_708,
  title = {{Hierarchical Graph Convolution Network for Traffic Forecasting}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2021},
  url = {https://aaai.org/papers/00151-hierarchical-graph-convolution-network-for-traffic-forecasting/},
}

@inproceedings{aaai2021_coupled_337,
  title = {{Coupled Layer-wise Graph Convolution for Transportation Demand Prediction}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2021},
  url = {https://aaai.org/papers/04617-coupled-layer-wise-graph-convolution-for-transportation-demand-prediction/},
}

@inproceedings{aaai2024_spatio_7391,
  title = {{Spatio-Temporal Pivotal Graph Neural Networks for Traffic Flow Forecasting}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/28707},
}

@inproceedings{aaai2020_semi_100298,
  title = {{Semi-Supervised Hierarchical Recurrent Graph Neural Network for City-Wide Parking Availability Prediction}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2020},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/5471},
}

@inproceedings{aaai2025_spatiotemporal_10809,
  title = {{Spatiotemporal-aware Trend-Seasonality Decomposition Network for Traffic Flow Forecasting}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/33247},
}

@inproceedings{aaai2025_efficient_8921,
  title = {{Efficient Traffic Prediction Through Spatio-Temporal Distillation}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/32096},
}

@inproceedings{aaai2024_towards_7587,
  title = {{Towards Dynamic Spatial-Temporal Graph Learning: A Decoupled Perspective}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/28759},
}

@inproceedings{aaai2025_dual_8824,
  title = {{Dual-Channel Interactive Graph Transformer for Traffic Classification with Message-Aware Flow Representation}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/32050},
}

@inproceedings{aaai2024_teltrans_7510,
  title = {{TelTrans: Applying Multi-Type Telecom Data to Transportation Evaluation and Prediction via Multifaceted Graph Modeling}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/30331},
}

@inproceedings{aaai2025_responsive_10530,
  title = {{Responsive Dynamic Graph Disentanglement for Metro Flow Forecasting}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/33272},
}

@inproceedings{iclr2024_testam_34275,
  title = {{TESTAM: A Time-Enhanced Spatio-Temporal Attention Model with Mixture of Experts}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/18800},
}

@inproceedings{aaai2026_hyperd_106292,
  title = {{HyperD: Hybrid Periodicity Decoupling Framework for Traffic Forecasting}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/38599},
}

@inproceedings{aaai2026_vite_106501,
  title = {{ViTE: Virtual Graph Trajectory Expert Router for Pedestrian Trajectory Prediction}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/38808},
}

@inproceedings{aaai2024_i_6245,
  title = {{I Open at the Close: A Deep Reinforcement Learning Evaluation of Open Streets Initiatives}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/30250},
}

@inproceedings{iclr2025_expand_81432,
  title = {{Expand and Compress: Exploring Tuning Principles for Continual Spatio-Temporal Graph Forecasting}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/30341},
}

@inproceedings{aaai2026_adaptive_106288,
  title = {{Adaptive Frequency Pathways for Spatiotemporal Forecasting}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/38595},
}

@inproceedings{aaai2026_unlocking_100032,
  title = {{Unlocking Dynamic Inter-Client Spatial Dependencies: A Federated Spatio-temporal Graph Learning Method for Traffic Flow Forecasting}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/37083},
}

@inproceedings{aaai2026_meta_106392,
  title = {{Meta Dynamic Graph for Traffic Flow Prediction}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/38699},
}

@inproceedings{icml2025_robust_48657,
  title = {{Robust Spatio-Temporal Centralized Interaction for OOD Learning}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/43964},
}

@inproceedings{icml2026_osm_50435,
  title = {{OSM+: Billion-Level Open Street Map Dataset for City-wide Experiments}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=CMeeyJzWZ5},
}

@inproceedings{iclr2026_lightweight_84982,
  title = {{Lightweight Spatio-Temporal Modeling via Temporally Shifted Distillation for Real-Time Accident Anticipation}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2026},
  url = {https://openreview.net/forum?id=8zzfTSVds2},
}

@inproceedings{iclr2026_a_86047,
  title = {{A General Spatio-Temporal Backbone with Scalable Contextual Pattern Bank for Urban Continual Forecasting}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2026},
  url = {https://openreview.net/forum?id=LHSea6DI8U},
}

@inproceedings{iclr2026_micro_87806,
  title = {{Micro-Macro Coupled Koopman Modeling on Graph for Traffic Flow Prediction}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2026},
  url = {https://openreview.net/forum?id=fhDqFk4DgI},
}