% Key papers for Inductive bias and minimal representations (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{neurips2020_what_61096,
  title = {{What Makes for Good Views for Contrastive Learning?}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/17444},
}

@inproceedings{neurips2020_hard_59990,
  title = {{Hard Negative Mixing for Contrastive Learning}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/16984},
}

@inproceedings{cvpr2021_adco_16565,
  title = {{AdCo: Adversarial Contrast for Efficient Learning of Unsupervised Representations From Self-Trained Negative Adversaries}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2021},
}

@inproceedings{iclr2021_what_30105,
  title = {{What Should Not Be Contrastive in Contrastive Learning}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2021},
  url = {https://iclr.cc/virtual/2021/poster/2809},
}

@inproceedings{cvpr2022_use_20155,
  title = {{Use All the Labels: A Hierarchical Multi-Label Contrastive Learning Framework}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2022},
}

@inproceedings{aaai2022_mutual_2452,
  title = {{Mutual Contrastive Learning for Visual Representation Learning}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2022},
  url = {https://aaai.org/papers/03045-mutual-contrastive-learning-for-visual-representation-learning/},
}

@inproceedings{cvpr2022_rethinking_19724,
  title = {{Rethinking Minimal Sufficient Representation in Contrastive Learning}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2022},
}

@inproceedings{cvpr2023_best_20457,
  title = {{Best of Both Worlds: Multimodal Contrastive Learning With Tabular and Imaging Data}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2023},
  url = {https://cvpr.thecvf.com/virtual/2023/poster/22092},
}

@inproceedings{aaai2023_hierarchical_3831,
  title = {{Hierarchical Consistent Contrastive Learning for Skeleton-Based Action Recognition with Growing Augmentations}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2023},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/25451},
}

@inproceedings{icml2023_contrast_41681,
  title = {{Contrast with Reconstruct: Contrastive 3D Representation Learning Guided by Generative Pretraining}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2023},
  url = {https://icml.cc/virtual/2023/poster/25160},
}

@inproceedings{icml2021_clocs_39119,
  title = {{CLOCS: Contrastive Learning of Cardiac Signals Across Space, Time, and Patients}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2021},
  url = {https://icml.cc/virtual/2021/poster/8461},
}

@inproceedings{icml2021_contrastive_39172,
  title = {{Contrastive Learning Inverts the Data Generating Process}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2021},
  url = {https://icml.cc/virtual/2021/poster/9643},
}

@inproceedings{cvpr2023_difficulty_20794,
  title = {{Difficulty-Based Sampling for Debiased Contrastive Representation Learning}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2023},
  url = {https://cvpr.thecvf.com/virtual/2023/poster/21735},
}

@inproceedings{iclr2022_chaos_31045,
  title = {{Chaos is a Ladder: A New Theoretical Understanding of Contrastive Learning via Augmentation Overlap}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2022},
  url = {https://iclr.cc/virtual/2022/poster/6659},
}

@inproceedings{neurips2020_debiased_59637,
  title = {{Debiased Contrastive Learning}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/17803},
}

@inproceedings{icml2022_understanding_41300,
  title = {{Understanding Contrastive Learning Requires Incorporating Inductive Biases}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2022},
  url = {https://icml.cc/virtual/2022/poster/18173},
}

@inproceedings{aaai2023_self_4640,
  title = {{Self-Contrastive Learning: Single-Viewed Supervised Contrastive Framework Using Sub-network}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2023},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/25091},
}

@inproceedings{icml2021_self_39933,
  title = {{Self-Damaging Contrastive Learning}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2021},
  url = {https://icml.cc/virtual/2021/poster/10081},
}

@inproceedings{neurips2022_metamask_65651,
  title = {{MetaMask: Revisiting Dimensional Confounder for Self-Supervised Learning}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2022},
  url = {https://nips.cc/virtual/2022/poster/55384},
}

@inproceedings{icml2021_toward_40038,
  title = {{Toward Understanding the Feature Learning Process of Self-supervised Contrastive Learning}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2021},
  url = {https://icml.cc/virtual/2021/poster/8579},
}

@inproceedings{neurips2024_your_73458,
  title = {{Your contrastive learning problem is secretly a distribution alignment problem}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/94010},
}

@inproceedings{aaai2025_enhancing_8953,
  title = {{Enhancing Contrastive Learning Inspired by the Philosophy of “The Blind Men and the Elephant”}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/34425},
}

@inproceedings{iclr2024_an_35322,
  title = {{An Investigation of Representation and Allocation Harms in Contrastive Learning}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/17751},
}

@inproceedings{icml2025_weakly_47663,
  title = {{Weakly-Supervised Contrastive Learning for Imprecise Class Labels}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/44934},
}

@inproceedings{icml2025_an_47914,
  title = {{An Augmentation-Aware Theory for Self-Supervised Contrastive Learning}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/44689},
}

@inproceedings{icml2025_how_48139,
  title = {{How does Labeling Error Impact Contrastive Learning? A Perspective from Data Dimensionality Reduction}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/44470},
}

@inproceedings{icml2026_the_50511,
  title = {{The Loss Is Not Enough: Sampling Conditions and Inductive Bias in Contrastive Representation Learning}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=D5rimtisOc},
}

@inproceedings{icml2026_bayesian_54135,
  title = {{Bayesian Gated Non-Negative Contrastive Learning}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=mIRio0hWWI},
}

@inproceedings{icml2026_statistical_55319,
  title = {{Statistical Consistency and Generalization of Contrastive Representation Learning}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=xixoixLXCr},
}

@inproceedings{neurips2025_mitigating_77399,
  title = {{Mitigating Spurious Features in Contrastive Learning with Spectral Regularization}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=TPMsCus3r0},
}

@inproceedings{neurips2025_caligcl_78013,
  title = {{CaliGCL: Calibrated Graph Contrastive Learning via Partitioned Similarity and Consistency Discrimination}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=aAxHUzTdhe},
}

@inproceedings{neurips2025_enhancing_79357,
  title = {{Enhancing Contrastive Learning with Variable Similarity}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=oUf6lhK52B},
}

@inproceedings{neurips2025_multi_79711,
  title = {{Multi-modal contrastive learning adapts to intrinsic dimensions of shared latent variables}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=sCgYsBVIVG},
}

@inproceedings{neurips2025_adaptive_79745,
  title = {{Adaptive and Multi-scale Affinity Alignment for Hierarchical Contrastive Learning}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=sZ22INHr9H},
}

@inproceedings{iclr2025_projection_81758,
  title = {{Projection Head is Secretly an Information Bottleneck}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/30021},
}

@inproceedings{iclr2025_contrastive_82489,
  title = {{Contrastive Learning from Synthetic Audio Doppelgängers}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/29305},
}

@inproceedings{iclr2025_mathbb_82722,
  title = {{\$mathbbX\$-Sample Contrastive Loss: Improving Contrastive Learning with Sample Similarity Graphs}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/29076},
}

@inproceedings{iclr2026_difficult_84674,
  title = {{Difficult Examples Hurt Unsupervised Contrastive Learning: A Theoretical Perspective}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2026},
  url = {https://openreview.net/forum?id=5LMdnUdAoy},
}

@inproceedings{iclr2026_maximizing_87072,
  title = {{Maximizing Incremental Information Entropy for Contrastive Learning}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2026},
  url = {https://openreview.net/forum?id=XL7ValpExh},
}

@inproceedings{neurips2026_contrast_91261,
  title = {{Contrast encodes inductive bias: separating slow noise from dynamics in predictive representation learning}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2026},
  url = {https://neurips.cc/virtual/2026/poster/149353},
}