% Key papers for Augmentation-free graph learning (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{aaai2022_augmentation_1759,
  title = {{Augmentation-Free Self-Supervised Learning on Graphs}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2022},
  url = {https://aaai.org/papers/07372-augmentation-free-self-supervised-learning-on-graphs/},
}

@inproceedings{aaai2023_spectral_4721,
  title = {{Spectral Feature Augmentation for Graph Contrastive Learning and Beyond}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2023},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/26336},
}

@inproceedings{aaai2024_gamc_6081,
  title = {{GAMC: An Unsupervised Method for Fake News Detection Using Graph Autoencoder with Masking}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/27788},
}

@inproceedings{cvpr2023_transg_22406,
  title = {{TranSG: Transformer-Based Skeleton Graph Prototype Contrastive Learning With Structure-Trajectory Prompted Reconstruction for Person Re-Identification}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2023},
  url = {https://cvpr.thecvf.com/virtual/2023/poster/22599},
}

@inproceedings{aaai2024_propagation_7015,
  title = {{Propagation Tree Is Not Deep: Adaptive Graph Contrastive Learning Approach for Rumor Detection}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/27757},
}

@inproceedings{aaai2022_regularizing_2628,
  title = {{Regularizing Graph Neural Networks via Consistency-Diversity Graph Augmentations}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2022},
  url = {https://aaai.org/papers/03913-regularizing-graph-neural-networks-via-consistency-diversity-graph-augmentations/},
}

@inproceedings{neurips2022_augmentations_65734,
  title = {{Augmentations in Hypergraph Contrastive Learning: Fabricated and Generative}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2022},
  url = {https://nips.cc/virtual/2022/poster/54524},
}

@inproceedings{iclr2023_automated_33340,
  title = {{Automated Data Augmentations for Graph Classification}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2023},
  url = {https://iclr.cc/virtual/2023/poster/12034},
}

@inproceedings{neurips2022_label_66146,
  title = {{Label-invariant Augmentation for Semi-Supervised Graph Classification}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2022},
  url = {https://nips.cc/virtual/2022/poster/53785},
}

@inproceedings{aaai2023_graph_3795,
  title = {{Graph Component Contrastive Learning for Concept Relatedness Estimation}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2023},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/26568},
}

@inproceedings{neurips2021_multi_62074,
  title = {{Multi-view Contrastive Graph Clustering}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2021},
  url = {https://nips.cc/virtual/2021/poster/28745},
}

@inproceedings{aaai2025_through_10997,
  title = {{Through the Dual-Prism: A Spectral Perspective on Graph Data Augmentation for Graph Classifications}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/35467},
}

@inproceedings{icml2023_randomized_43172,
  title = {{Randomized Schur Complement Views for Graph Contrastive Learning}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2023},
  url = {https://icml.cc/virtual/2023/poster/24371},
}

@inproceedings{icml2025_learn_48272,
  title = {{Learn Beneficial Noise as Graph Augmentation}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/44340},
}

@inproceedings{aaai2026_from_106381,
  title = {{From Semantics to Spectrum: A New Lens on Graph Augmentation Strategy}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/38688},
}

@inproceedings{aaai2026_graph_108458,
  title = {{Graph-augmented and Over-smoothing-resistant Contrastive Clustering for Short Text}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/40810},
}

@inproceedings{icml2024_unsupervised_43662,
  title = {{Unsupervised Episode Generation for Graph Meta-learning}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/34790},
}

@inproceedings{icml2026_from_53309,
  title = {{From Moments to Models: Graphon-Mixture Learning for Mixup and Contrastive Learning}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=eGJEOl9vAg},
}

@inproceedings{icml2026_gcib_53901,
  title = {{GCIB: Graph Contrastive Information Bottleneck for Multi-Behavior Recommendation}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=jq7Nk1p7mW},
}

@inproceedings{neurips2025_hybrid_78512,
  title = {{Hybrid-Collaborative Augmentation and Contrastive Sample Adaptive-Differential Awareness for Robust Attributed Graph Clustering}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=fb7maZToPl},
}

@inproceedings{icml2025_causal_46664,
  title = {{Causal Invariance-aware Augmentation for Brain Graph Contrastive Learning}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/45908},
}

@inproceedings{icml2025_towards_46935,
  title = {{Towards Understanding Parametric Generalized Category Discovery on Graphs}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/45645},
}

@inproceedings{icml2025_equivalence_47726,
  title = {{Equivalence is All: A Unified View for Self-supervised Graph Learning}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/44874},
}

@inproceedings{icml2026_h_50440,
  title = {{H\$^2\$CL: Heterogeneity-Aware Hypergraph Contrastive Learning for Robust Representation Learning}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=CPEld7VE6T},
}