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

@inproceedings{aaai2018_community_99826,
  title = {{Community Detection in Attributed Graphs: An Embedding Approach}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2018},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/11274},
}

@inproceedings{aaai2016_semantic_104734,
  title = {{Semantic Community Identification in Large Attribute Networks}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2016},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/9977},
}

@inproceedings{aaai2017_semantic_99777,
  title = {{Semantic Proximity Search on Heterogeneous Graph by Proximity Embedding}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2017},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/10486},
}

@inproceedings{neurips2019_end_58213,
  title = {{End to end learning and optimization on graphs}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/13617},
}

@inproceedings{iclr2019_large_29202,
  title = {{Large Scale Graph Learning From Smooth Signals}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2019},
  url = {https://iclr.cc/virtual/2019/poster/661},
}

@inproceedings{neurips2019_diskann_58151,
  title = {{DiskANN: Fast Accurate Billion-point Nearest Neighbor Search on a Single Node}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/14308},
}

@inproceedings{cvpr2021_combinatorial_16722,
  title = {{Combinatorial Learning of Graph Edit Distance via Dynamic Embedding}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2021},
}

@inproceedings{cvpr2019_biologically_13897,
  title = {{Biologically-Constrained Graphs for Global Connectomics Reconstruction}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2019},
}

@inproceedings{aaai2020_reduction_101066,
  title = {{Reduction and Local Search for Weighted Graph Coloring Problem}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2020},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/5624},
}

@inproceedings{neurips2018_practical_57522,
  title = {{Practical Methods for Graph Two-Sample Testing}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/11307},
}

@inproceedings{aaai2019_distributed_101656,
  title = {{Distributed PageRank Computation: An Improved Theoretical Study}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2019},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/4363},
}

@inproceedings{aaai2018_axioms_100991,
  title = {{Axioms for Distance-Based Centralities}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2018},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/11441},
}

@inproceedings{neurips2022_greed_63827,
  title = {{GREED: A Neural Framework for Learning Graph Distance Functions}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2022},
  url = {https://nips.cc/virtual/2022/poster/54507},
}

@inproceedings{aaai2020_telltail_101973,
  title = {{TellTail: Fast Scoring and Detection of Dense Subgraphs}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2020},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/5835},
}

@inproceedings{aaai2023_scalable_4611,
  title = {{Scalable Edge Blocking Algorithms for Defending Active Directory Style Attack Graphs}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2023},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/25701},
}

@inproceedings{icml2016_cross_35780,
  title = {{Cross-Graph Learning of Multi-Relational Associations}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2016},
  url = {https://proceedings.mlr.press/v48/liuf16.html},
}

@inproceedings{aaai2024_lanegraph2seq_6418,
  title = {{LaneGraph2Seq: Lane Topology Extraction with Language Model via Vertex-Edge Encoding and Connectivity Enhancement}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/28248},
}

@inproceedings{neurips2021_slow_63013,
  title = {{Slow Learning and Fast Inference: Efficient Graph Similarity Computation via Knowledge Distillation}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2021},
  url = {https://nips.cc/virtual/2021/poster/26151},
}

@inproceedings{aaai2020_defending_100893,
  title = {{Defending with Shared Resources on a Network}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2020},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/5585},
}

@inproceedings{aaai2022_reconfiguring_2616,
  title = {{Reconfiguring Shortest Paths in Graphs}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2022},
  url = {https://aaai.org/papers/09758-reconfiguring-shortest-paths-in-graphs/},
}

@inproceedings{aaai2025_dimension_8750,
  title = {{Dimension Reduction with Locally Adjusted Graphs}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/35436},
}

@inproceedings{aaai2024_tree_7486,
  title = {{TREE-G: Decision Trees Contesting Graph Neural Networks}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/28979},
}

@inproceedings{aaai2025_grasp_9353,
  title = {{GraSP: Simple Yet Effective Graph Similarity Predictions}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/34450},
}

@inproceedings{iclr2024_core_35559,
  title = {{CoRe-GD: A Hierarchical Framework for Scalable Graph Visualization with GNNs}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/17514},
}

@inproceedings{neurips2024_faster_70362,
  title = {{Faster Local Solvers for Graph Diffusion Equations}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/96736},
}

@inproceedings{neurips2024_navigable_70694,
  title = {{Navigable Graphs for High-Dimensional Nearest Neighbor Search: Constructions and Limits}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/96430},
}

@inproceedings{neurips2024_graph_74264,
  title = {{Graph Edit Distance with General Costs Using Neural Set Divergence}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/93292},
}

@inproceedings{aaai2025_temporal_10946,
  title = {{Temporal Triadic Closure: Finding Dense Substructures in Social Networks That Evolve over Time}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/34899},
}

@inproceedings{icml2024_differentiable_44375,
  title = {{Differentiable Mapper for Topological Optimization of Data Representation}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/34077},
}

@inproceedings{neurips2024_why_71645,
  title = {{Why the Metric Backbone Preserves Community Structure}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/95632},
}

@inproceedings{neurips2024_fugal_72254,
  title = {{FUGAL: Feature-fortified Unrestricted Graph Alignment}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/95090},
}

@inproceedings{iclr2024_graph_34994,
  title = {{Graph Parsing Networks}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/18080},
}

@inproceedings{icml2025_grail_47118,
  title = {{GRAIL: Graph Edit Distance and Node Alignment using LLM-Generated Code}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/45469},
}

@inproceedings{icml2025_what_48988,
  title = {{What Makes a Good Feedforward Computational Graph?}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/43635},
}

@inproceedings{neurips2024_challenges_72935,
  title = {{Challenges of Generating Structurally Diverse Graphs}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/94476},
}

@inproceedings{neurips2024_ugc_73813,
  title = {{UGC: Universal Graph Coarsening}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/93695},
}

@inproceedings{neurips2025_taxonomy_78502,
  title = {{Taxonomy of reduction matrices for Graph Coarsening}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=fUhWmqCnqW},
}

@inproceedings{neurips2025_distance_80123,
  title = {{Distance Adaptive Beam Search for Provably Accurate Graph-Based Nearest Neighbor Search}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=wORrUUmffG},
}

@inproceedings{iclr2026_gelato_84782,
  title = {{Gelato: Graph Edit Distance via Autoregressive Neural Combinatorial Optimization}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2026},
  url = {https://openreview.net/forum?id=6ZTcLNmguc},
}