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

@inproceedings{cvpr2019_efficient_14136,
  title = {{Efficient Parameter-Free Clustering Using First Neighbor Relations}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2019},
}

@inproceedings{neurips2017_inhomogeneous_56388,
  title = {{Inhomogeneous Hypergraph Clustering with Applications}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2017},
  url = {https://nips.cc/virtual/2017/poster/9018},
}

@inproceedings{icml2018_submodular_37023,
  title = {{Submodular Hypergraphs: p-Laplacians, Cheeger Inequalities and Spectral Clustering}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2018},
  url = {https://icml.cc/virtual/2018/poster/2044},
}

@inproceedings{neurips2016_clustering_55623,
  title = {{Clustering with Same-Cluster Queries}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2016},
  url = {https://nips.cc/virtual/2016/poster/7219},
}

@inproceedings{aaai2018_flic_104027,
  title = {{FLIC: Fast Linear Iterative Clustering With Active Search}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2018},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/12286},
}

@inproceedings{aaai2019_spectral_101622,
  title = {{Spectral Clustering in Heterogeneous Information Networks}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2019},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/4328},
}

@inproceedings{neurips2016_clustering_55621,
  title = {{Clustering Signed Networks with the Geometric Mean of Laplacians}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2016},
  url = {https://nips.cc/virtual/2016/poster/7239},
}

@inproceedings{aaai2018_exact_101096,
  title = {{Exact Clustering via Integer Programming and Maximum Satisfiability}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2018},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/11519},
}

@inproceedings{icml2019_improved_37440,
  title = {{Improved Parallel Algorithms for Density-Based Network Clustering}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2019},
  url = {https://icml.cc/virtual/2019/poster/3626},
}

@inproceedings{neurips2019_subquadratic_59038,
  title = {{Subquadratic High-Dimensional Hierarchical Clustering}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/14140},
}

@inproceedings{aaai2018_saga_102383,
  title = {{SAGA: A Submodular Greedy Algorithm for Group Recommendation}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2018},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/11650},
}

@inproceedings{neurips2016_optimal_55920,
  title = {{Optimal Cluster Recovery in the Labeled Stochastic Block Model}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2016},
  url = {https://nips.cc/virtual/2016/poster/7028},
}

@inproceedings{neurips2020_efficient_59758,
  title = {{Efficient Clustering Based On A Unified View Of \$K\$-means And Ratio-cut}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/17639},
}

@inproceedings{icml2017_composing_36102,
  title = {{Composing Tree Graphical Models with Persistent Homology Features for Clustering Mixed-Type Data}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2017},
  url = {https://icml.cc/virtual/2017/poster/504},
}

@inproceedings{neurips2018_bipartite_56917,
  title = {{Bipartite Stochastic Block Models with Tiny Clusters}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/11385},
}

@inproceedings{icml2018_partial_36918,
  title = {{Partial Optimality and Fast Lower Bounds for Weighted Correlation Clustering}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2018},
  url = {https://icml.cc/virtual/2018/poster/2206},
}

@inproceedings{icml2021_hierarchical_39418,
  title = {{Hierarchical Agglomerative Graph Clustering in Nearly-Linear Time}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2021},
  url = {https://icml.cc/virtual/2021/poster/9207},
}

@inproceedings{neurips2019_correlation_58058,
  title = {{Correlation Clustering with Adaptive Similarity Queries}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/14206},
}

@inproceedings{neurips2020_discovering_59713,
  title = {{Discovering conflicting groups in signed networks}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/18024},
}

@inproceedings{aaai2017_scalable_104537,
  title = {{Scalable Algorithm for Higher-Order Co-Clustering via Random Sampling}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2017},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/10914},
}

@inproceedings{aaai2024_equivalence_5873,
  title = {{Equivalence between Graph Spectral Clustering and Column Subset Selection (Student Abstract)}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/30521},
}

@inproceedings{icml2024_combinatorial_43930,
  title = {{Combinatorial Approximations for Cluster Deletion: Simpler, Faster, and Better}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/34522},
}

@inproceedings{neurips2024_scalable_73111,
  title = {{Scalable DBSCAN with Random Projections}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/94318},
}

@inproceedings{neurips2025_clustering_75525,
  title = {{Clustering via Hedonic Games: New Concepts and Algorithms}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=96I0XnrjkQ},
}

@inproceedings{neurips2024_efficient_70526,
  title = {{Efficient Centroid-Linkage Clustering}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/96585},
}

@inproceedings{neurips2025_improved_74703,
  title = {{Improved Approximation Algorithms for Chromatic and Pseudometric-Weighted Correlation Clustering}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=0JSolJVzjd},
}

@inproceedings{aaai2024_approximation_5203,
  title = {{Approximation Scheme for Weighted Metric Clustering via Sherali-Adams}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/28629},
}

@inproceedings{icml2024_dynamic_43394,
  title = {{Dynamic Correlation Clustering in Sublinear Update Time}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/35058},
}

@inproceedings{icml2024_a_44213,
  title = {{A Near-Linear Time Approximation Algorithm for Beyond-Worst-Case Graph Clustering}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/34239},
}

@inproceedings{icml2024_new_45020,
  title = {{New Bounds on the Cohesion of Complete-link and Other Linkage Methods for Agglomerative Clustering}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/33432},
}

@inproceedings{icml2025_generalization_46506,
  title = {{Generalization Performance of Ensemble Clustering: From Theory to Algorithm}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/46061},
}

@inproceedings{icml2025_towards_47052,
  title = {{Towards Better-than-2 Approximation for Constrained Correlation Clustering}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/45533},
}

@inproceedings{icml2025_correlation_47181,
  title = {{Correlation Clustering Beyond the Pivot Algorithm}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/45406},
}

@inproceedings{icml2025_edge_47237,
  title = {{Edge-Colored Clustering in Hypergraphs: Beyond Minimizing Unsatisfied Edges}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/45350},
}

@inproceedings{icml2025_sparse_47802,
  title = {{Sparse-pivot: Dynamic correlation clustering for node insertions}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/44798},
}

@inproceedings{icml2025_revisiting_48339,
  title = {{Revisiting Instance-Optimal Cluster Recovery in the Labeled Stochastic Block Model}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/44276},
}

@inproceedings{icml2025_dynamic_48813,
  title = {{Dynamic Similarity Graph Construction with Kernel Density Estimation}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/43809},
}

@inproceedings{neurips2024_on_70268,
  title = {{On the cohesion and separability of average-link for hierarchical agglomerative clustering}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/96821},
}

@inproceedings{neurips2024_query_72536,
  title = {{Query-Efficient Correlation Clustering with Noisy Oracle}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/94832},
}

@inproceedings{neurips2024_on_73580,
  title = {{On the Robustness of Spectral Algorithms for Semirandom Stochastic Block Models}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/93905},
}