% Key papers for Graph rewiring and scalable message passing (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{cvpr2020_conv_15285,
  title = {{Conv-MPN: Convolutional Message Passing Neural Network for Structured Outdoor Architecture Reconstruction}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2020},
}

@inproceedings{aaai2023_dropmessage_3504,
  title = {{DropMessage: Unifying Random Dropping for Graph Neural Networks}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2023},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/25545},
}

@inproceedings{cvpr2021_hybrid_17144,
  title = {{Hybrid Message Passing With Performance-Driven Structures for Facial Action Unit Detection}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2021},
}

@inproceedings{aaai2020_message_103066,
  title = {{Message Passing Attention Networks for Document Understanding}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2020},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/6376},
}

@inproceedings{aaai2024_textgt_7535,
  title = {{TextGT: A Double-View Graph Transformer on Text for Aspect-Based Sentiment Analysis}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29911},
}

@inproceedings{iclr2022_understanding_30912,
  title = {{Understanding over-squashing and bottlenecks on graphs via curvature}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2022},
  url = {https://iclr.cc/virtual/2022/poster/6849},
}

@inproceedings{aaai2022_graph_2165,
  title = {{Graph Convolutional Networks with Dual Message Passing for Subgraph Isomorphism Counting and Matching}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2022},
  url = {https://aaai.org/papers/07594-graph-convolutional-networks-with-dual-message-passing-for-subgraph-isomorphism-counting-and-matching/},
}

@inproceedings{icml2023_on_43059,
  title = {{On Over-Squashing in Message Passing Neural Networks: The Impact of Width, Depth, and Topology}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2023},
  url = {https://icml.cc/virtual/2023/poster/24077},
}

@inproceedings{neurips2021_diverse_61325,
  title = {{Diverse Message Passing for Attribute with Heterophily}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2021},
  url = {https://nips.cc/virtual/2021/poster/28113},
}

@inproceedings{neurips2022_not_63643,
  title = {{Not too little, not too much: a theoretical analysis of graph (over)smoothing}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2022},
  url = {https://nips.cc/virtual/2022/poster/53409},
}

@inproceedings{iclr2023_ordered_33362,
  title = {{Ordered GNN: Ordering Message Passing to Deal with Heterophily and Over-smoothing}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2023},
  url = {https://iclr.cc/virtual/2023/poster/10760},
}

@inproceedings{neurips2020_how_60024,
  title = {{How hard is to distinguish graphs with graph neural networks?}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/17690},
}

@inproceedings{icml2023_graph_41970,
  title = {{Graph Inductive Biases in Transformers without Message Passing}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2023},
  url = {https://icml.cc/virtual/2023/poster/23715},
}

@inproceedings{aaai2022_self_2711,
  title = {{Self-Supervised Graph Neural Networks via Diverse and Interactive Message Passing}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2022},
  url = {https://aaai.org/papers/04327-self-supervised-graph-neural-networks-via-diverse-and-interactive-message-passing/},
}

@inproceedings{neurips2020_neural_60400,
  title = {{Neural Message Passing for Multi-Relational Ordered and Recursive Hypergraphs}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/16908},
}

@inproceedings{neurips2022_long_65739,
  title = {{Long Range Graph Benchmark}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2022},
  url = {https://nips.cc/virtual/2022/poster/55719},
}

@inproceedings{iclr2023_acmp_32027,
  title = {{ACMP: Allen-Cahn Message Passing with Attractive and Repulsive Forces for Graph Neural Networks}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2023},
  url = {https://iclr.cc/virtual/2023/poster/11740},
}

@inproceedings{icml2023_ewald_43133,
  title = {{Ewald-based Long-Range Message Passing for Molecular Graphs}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2023},
  url = {https://icml.cc/virtual/2023/poster/23626},
}

@inproceedings{icml2016_metadata_35902,
  title = {{Metadata-conscious anonymous messaging}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2016},
  url = {https://proceedings.mlr.press/v48/fanti16.html},
}

@inproceedings{aaai2024_moderate_6667,
  title = {{Moderate Message Passing Improves Calibration: A Universal Way to Mitigate Confidence Bias in Graph Neural Networks}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/30167},
}

@inproceedings{iclr2024_probabilistically_34515,
  title = {{Probabilistically Rewired Message-Passing Neural Networks}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/18559},
}

@inproceedings{neurips2024_pure_72625,
  title = {{Pure Message Passing Can Estimate Common Neighbor for Link Prediction}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/94755},
}

@inproceedings{neurips2024_towards_70418,
  title = {{Towards Dynamic Message Passing on Graphs}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/96687},
}

@inproceedings{neurips2024_spectral_71193,
  title = {{Spectral Graph Pruning Against Over-Squashing and Over-Smoothing}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/96038},
}

@inproceedings{aaai2025_faithful_9138,
  title = {{Faithful and Accurate Self-Attention Attribution for Message Passing Neural Networks via the Computation Tree Viewpoint}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/34254},
}

@inproceedings{icml2024_panda_44048,
  title = {{PANDA: Expanded Width-Aware Message Passing Beyond Rewiring}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/34404},
}

@inproceedings{icml2024_verifying_45316,
  title = {{Verifying message-passing neural networks via topology-based bounds tightening}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/33136},
}

@inproceedings{neurips2024_probabilistic_71718,
  title = {{Probabilistic Graph Rewiring via Virtual Nodes}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/95568},
}

@inproceedings{neurips2024_sequential_72846,
  title = {{Sequential Signal Mixing Aggregation for Message Passing Graph Neural Networks}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/94554},
}

@inproceedings{neurips2024_how_72970,
  title = {{How Does Message Passing Improve Collaborative Filtering?}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/94445},
}

@inproceedings{neurips2025_return_79345,
  title = {{Return of ChebNet: Understanding and Improving an Overlooked GNN on Long Range Tasks}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=oLyfML1Qze},
}

@inproceedings{neurips2025_deeper_80319,
  title = {{Deeper with Riemannian Geometry: Overcoming Oversmoothing and Oversquashing for Graph Foundation Models}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=yNej0aGtAZ},
}

@inproceedings{iclr2024_conformal_34990,
  title = {{Conformal Inductive Graph Neural Networks}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/18084},
}

@inproceedings{icml2025_best_46735,
  title = {{Best of Both Worlds: Advantages of Hybrid Graph Sequence Models}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/45837},
}

@inproceedings{icml2025_adaptive_47691,
  title = {{Adaptive Message Passing: A General Framework to Mitigate Oversmoothing, Oversquashing, and Underreaching}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/44906},
}

@inproceedings{neurips2024_graph_74088,
  title = {{Graph Coarsening with Message-Passing Guarantees}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/93445},
}

@inproceedings{iclr2025_training_80738,
  title = {{Training-Free Message Passing for Learning on Hypergraphs}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/31030},
}

@inproceedings{iclr2025_the_81377,
  title = {{The Effectiveness of Curvature-Based Rewiring and the Role of Hyperparameters in GNNs Revisited}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/30396},
}