% Key papers for Zeroth-order training methods (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{neurips2019_zo_59211,
  title = {{ZO-AdaMM: Zeroth-Order Adaptive Momentum Method for Black-Box Optimization}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/13812},
}

@inproceedings{iclr2020_learning_29919,
  title = {{Learning to Learn by Zeroth-Order Oracle}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2020},
  url = {https://openreview.net/forum?id=ryxz8CVYDH},
}

@inproceedings{icml2022_improve_40679,
  title = {{Improve Single-Point Zeroth-Order Optimization Using High-Pass and Low-Pass Filters}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2022},
  url = {https://icml.cc/virtual/2022/poster/16791},
}

@inproceedings{neurips2025_pseuzo_79828,
  title = {{PseuZO: Pseudo-Zeroth-Order Algorithm for Training Deep Neural Networks}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=tM4cHBD7kD},
}

@inproceedings{neurips2025_pazo_78099,
  title = {{PaZO: Preconditioned Accelerated Zeroth-Order Optimization for Fine-Tuning LLMs}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=b2IU6QOOfo},
}

@inproceedings{aaai2025_leveraging_9777,
  title = {{Leveraging First and Zeroth-Order Gradient to Address Imbalanced Black-Box Prompt Tuning via Minimax Optimization}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/34397},
}

@inproceedings{neurips2021_on_62637,
  title = {{On the Convergence of Prior-Guided Zeroth-Order Optimization Algorithms}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2021},
  url = {https://nips.cc/virtual/2021/poster/26297},
}

@inproceedings{icml2025_refining_47105,
  title = {{Refining Adaptive Zeroth-Order Optimization at Ease}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/45481},
}

@inproceedings{icml2026_learning_52296,
  title = {{Learning Dynamics of Zeroth-Order Optimization: A Kernel Perspective}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=UTIylOfVUb},
}

@inproceedings{icml2026_revisiting_54244,
  title = {{Revisiting Zeroth-Order Hessian Approximation: A Single-Step Policy Optimization Lens}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=nEQYu4ndGA},
}

@inproceedings{icml2026_turning_54732,
  title = {{Turning Stale Gradients into Stable Gradients: Coherent Coordinate Descent with Implicit Landscape Smoothing for Lightweight Zeroth-Order Optimization}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=s1CYkVHVvf},
}

@inproceedings{icml2026_zeroth_54745,
  title = {{Zeroth-Order Optimization at the Edge of Stability}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=s87tQaKAER},
}

@inproceedings{neurips2022_zeroth_63789,
  title = {{Zeroth-Order Hard-Thresholding: Gradient Error vs. Expansivity}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2022},
  url = {https://nips.cc/virtual/2022/poster/54390},
}

@inproceedings{neurips2024_relizo_74608,
  title = {{ReLIZO: Sample Reusable Linear Interpolation-based Zeroth-order Optimization}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/92981},
}

@inproceedings{neurips2025_improving_78252,
  title = {{Improving the Straight-Through Estimator with Zeroth-Order Information}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=ceTeM2Xl1n},
}

@inproceedings{neurips2025_zeroth_78803,
  title = {{Zeroth-Order Optimization Finds Flat Minima}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=iXy0ncNepZ},
}

@inproceedings{neurips2025_on_79647,
  title = {{On the Optimal Construction of Unbiased Gradient Estimators for Zeroth-Order Optimization}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=rVT1GK60Nt},
}

@inproceedings{iclr2023_zeroth_33142,
  title = {{Zeroth-Order Optimization with Trajectory-Informed Derivative Estimation}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2023},
  url = {https://iclr.cc/virtual/2023/poster/10721},
}

@inproceedings{iclr2024_new_34900,
  title = {{New Insight of Variance reduce in Zero-Order Hard-Thresholding: Mitigating Gradient Error and Expansivity Contradictions}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/18174},
}

@inproceedings{icml2020_min_38452,
  title = {{Min-Max Optimization without Gradients: Convergence and Applications to Black-Box Evasion and Poisoning Attacks}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2020},
  url = {https://icml.cc/virtual/2020/poster/5979},
}

@inproceedings{icml2026_romberg_50786,
  title = {{Romberg-Extrapolated Zeroth-Order Gradient Estimator: Higher-Order Bias Reduction with Preserved Leading Directional Variance}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=FiuJVpxuSX},
}

@inproceedings{icml2026_lozo_51841,
  title = {{LOZO+: Provably Efficient Zeroth-Order Fine-Tuning via Greedy Low-Rank Subspace Selection}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=QNScXX6osL},
}

@inproceedings{neurips2026_zo_91026,
  title = {{ZO-F2: Low-variance Fisher preconditioner via bilinear estimation for zeroth-order optimization}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2026},
  url = {https://neurips.cc/virtual/2026/poster/153380},
}