% Key papers for Equilibrium learning in zero-sum games (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{neurips2019_solving_58995,
  title = {{Solving a Class of Non-Convex Min-Max Games Using Iterative First Order Methods}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/14401},
}

@inproceedings{neurips2019_policy_58811,
  title = {{Policy Optimization Provably Converges to Nash Equilibria in Zero-Sum Linear Quadratic Games}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/14142},
}

@inproceedings{iclr2020_on_29525,
  title = {{On Solving Minimax Optimization Locally: A Follow-the-Ridge Approach}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2020},
  url = {https://openreview.net/forum?id=Hkx7_1rKwS},
}

@inproceedings{neurips2019_competitive_58013,
  title = {{Competitive Gradient Descent}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/13843},
}

@inproceedings{icml2020_implicit_38298,
  title = {{Implicit Learning Dynamics in Stackelberg Games: Equilibria Characterization, Convergence Analysis, and Empirical Study}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2020},
  url = {https://icml.cc/virtual/2020/poster/6403},
}

@inproceedings{icml2017_efficient_36173,
  title = {{Efficient Regret Minimization in Non-Convex Games}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2017},
  url = {https://icml.cc/virtual/2017/poster/581},
}

@inproceedings{neurips2020_a_59293,
  title = {{A mean-field analysis of two-player zero-sum games}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/17229},
}

@inproceedings{neurips2018_acceleration_56830,
  title = {{Acceleration through Optimistic No-Regret Dynamics}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/11381},
}

@inproceedings{neurips2019_poincar_58803,
  title = {{Poincaré Recurrence, Cycles and Spurious Equilibria in Gradient-Descent-Ascent for Non-Convex Non-Concave Zero-Sum Games}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/14587},
}

@inproceedings{iclr2020_convergence_29643,
  title = {{Convergence of Gradient Methods on Bilinear Zero-Sum Games}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2020},
  url = {https://openreview.net/forum?id=SJlVY04FwH},
}

@inproceedings{icml2020_stochastic_38794,
  title = {{Stochastic Hamiltonian Gradient Methods for Smooth Games}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2020},
  url = {https://icml.cc/virtual/2020/poster/6794},
}

@inproceedings{icml2021_learning_39538,
  title = {{Learning While Playing in Mean-Field Games: Convergence and Optimality}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2021},
  url = {https://icml.cc/virtual/2021/poster/9389},
}

@inproceedings{iclr2021_local_30084,
  title = {{Local Convergence Analysis of Gradient Descent Ascent with Finite Timescale Separation}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2021},
  url = {https://iclr.cc/virtual/2021/poster/3036},
}

@inproceedings{iclr2020_smooth_29270,
  title = {{Smooth markets: A basic mechanism for organizing gradient-based learners}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2020},
  url = {https://openreview.net/forum?id=B1xMEerYvB},
}

@inproceedings{iclr2023_a_32263,
  title = {{A Unified Approach to Reinforcement Learning, Quantal Response Equilibria, and Two-Player Zero-Sum Games}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2023},
  url = {https://iclr.cc/virtual/2023/poster/11487},
}

@inproceedings{icml2022_on_40921,
  title = {{On Last-Iterate Convergence Beyond Zero-Sum Games}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2022},
  url = {https://icml.cc/virtual/2022/poster/17011},
}

@inproceedings{icml2019_game_37388,
  title = {{Game Theoretic Optimization via Gradient-based Nikaido-Isoda Function}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2019},
  url = {https://icml.cc/virtual/2019/poster/4156},
}

@inproceedings{icml2020_finite_38221,
  title = {{Finite-Time Last-Iterate Convergence for Multi-Agent Learning in Games}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2020},
  url = {https://icml.cc/virtual/2020/poster/6358},
}

@inproceedings{neurips2022_on_64899,
  title = {{On the convergence of policy gradient methods to Nash equilibria in general stochastic games}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2022},
  url = {https://nips.cc/virtual/2022/poster/54489},
}

@inproceedings{neurips2022_finite_66196,
  title = {{Finite-Time Last-Iterate Convergence for Learning in Multi-Player Games}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2022},
  url = {https://nips.cc/virtual/2022/poster/52884},
}

@inproceedings{aaai2025_beyond_8251,
  title = {{Beyond Monotonicity: On the Convergence of Learning Algorithms in Standard Auction Games}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/33491},
}

@inproceedings{iclr2024_approximating_34786,
  title = {{Approximating Nash Equilibria in Normal-Form Games via Stochastic Optimization}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/18288},
}

@inproceedings{aaai2024_efficient_5807,
  title = {{Efficient Learning in Polyhedral Games via Best-Response Oracles}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/28812},
}

@inproceedings{aaai2025_last_9711,
  title = {{Last-iterate Convergence in Regularized Graphon Mean Field Game}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/33506},
}

@inproceedings{neurips2024_fast_73372,
  title = {{Fast Last-Iterate Convergence of Learning in Games Requires Forgetful Algorithms}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/94079},
}

@inproceedings{icml2024_adaptively_43648,
  title = {{Adaptively Perturbed Mirror Descent for Learning in Games}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/34804},
}

@inproceedings{icml2025_continuous_46258,
  title = {{Continuous-Time Analysis of Heavy Ball Momentum in Min-Max Games}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/46302},
}

@inproceedings{icml2025_solving_47969,
  title = {{Solving Zero-Sum Convex Markov Games}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/44636},
}

@inproceedings{icml2026_nash_50324,
  title = {{Nash Equilibria in Games with Playerwise Concave Coupling Constraints: Existence and Computation}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=BGmc3O41ZH},
}

@inproceedings{icml2026_offline_53134,
  title = {{Offline Two-Player Zero-Sum Markov Games with KL Regularization}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=cQD2wxFhFG},
}

@inproceedings{neurips2024_on_70332,
  title = {{On Tractable \$Phi\$-Equilibria in Non-Concave Games}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/96764},
}

@inproceedings{neurips2024_local_71423,
  title = {{Local and Adaptive Mirror Descents in Extensive-Form Games}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/95830},
}

@inproceedings{neurips2024_convergence_73417,
  title = {{Convergence of \$textlog(1/epsilon)\$ for Gradient-Based Algorithms in Zero-Sum Games without the Condition Number: A Smoothed Analysis}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/94042},
}

@inproceedings{neurips2024_accelerated_73666,
  title = {{Accelerated Regularized Learning in Finite N-Person Games}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/93826},
}

@inproceedings{neurips2025_solving_75254,
  title = {{Solving Neural Min-Max Games: The Role of Architecture, Initialization \& Dynamics}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=5xdbWUdM87},
}

@inproceedings{neurips2025_efficient_76501,
  title = {{Efficient Last-Iterate Convergence in Solving Extensive-Form Games}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=JzWtqd9CGJ},
}

@inproceedings{neurips2025_learning_78122,
  title = {{Learning in Stackelberg Mean Field Games: A Non-Asymptotic Analysis}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=bAZilxOZEp},
}

@inproceedings{neurips2025_last_78230,
  title = {{Last Iterate Convergence in Monotone Mean Field Games}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=cSomL3lHTa},
}

@inproceedings{neurips2025_from_79149,
  title = {{From Average-Iterate to Last-Iterate Convergence in Games: A Reduction and Its Applications}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=mG9xItYI0D},
}

@inproceedings{neurips2025_last_80001,
  title = {{Last-Iterate Convergence of Smooth Regret Matching\$^+\$ Variants in Learning Nash Equilibria}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=v771lscnlS},
}