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

@inproceedings{icml2016_an_35736,
  title = {{An optimal algorithm for the Thresholding Bandit Problem}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2016},
  url = {https://proceedings.mlr.press/v48/locatelli16.html},
}

@inproceedings{neurips2019_pure_58856,
  title = {{Pure Exploration with Multiple Correct Answers}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/14373},
}

@inproceedings{icml2020_concentration_38030,
  title = {{Concentration bounds for CVaR estimation: The cases of light-tailed and heavy-tailed distributions}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2020},
  url = {https://icml.cc/virtual/2020/poster/6104},
}

@inproceedings{icml2020_gamification_38240,
  title = {{Gamification of Pure Exploration for Linear Bandits}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2020},
  url = {https://icml.cc/virtual/2020/poster/6506},
}

@inproceedings{neurips2020_an_59370,
  title = {{An Empirical Process Approach to the Union Bound: Practical Algorithms for Combinatorial and Linear Bandits}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/18843},
}

@inproceedings{icml2017_identifying_36225,
  title = {{Identifying Best Interventions through Online Importance Sampling}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2017},
  url = {https://icml.cc/virtual/2017/poster/619},
}

@inproceedings{aaai2021_quantum_1216,
  title = {{Quantum Exploration Algorithms for Multi-Armed Bandits}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2021},
  url = {https://aaai.org/papers/10102-quantum-exploration-algorithms-for-multi-armed-bandits/},
}

@inproceedings{aaai2021_combinatorial_263,
  title = {{Combinatorial Pure Exploration with Full-Bandit or Partial Linear Feedback}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2021},
  url = {https://aaai.org/papers/07262-combinatorial-pure-exploration-with-full-bandit-or-partial-linear-feedback/},
}

@inproceedings{neurips2019_efficient_58195,
  title = {{Efficient Pure Exploration in Adaptive Round model}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/13770},
}

@inproceedings{icml2019_decentralized_37269,
  title = {{Decentralized Exploration in Multi-Armed Bandits}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2019},
  url = {https://icml.cc/virtual/2019/poster/3563},
}

@inproceedings{icml2020_combinatorial_38021,
  title = {{Combinatorial Pure Exploration for Dueling Bandit}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2020},
  url = {https://icml.cc/virtual/2020/poster/6272},
}

@inproceedings{aaai2024_thompson_7560,
  title = {{Thompson Sampling for Real-Valued Combinatorial Pure Exploration of Multi-Armed Bandit}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29355},
}

@inproceedings{neurips2019_making_58570,
  title = {{Making the Cut: A Bandit-based Approach to Tiered Interviewing}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/13614},
}

@inproceedings{icml2016_anytime_35739,
  title = {{Anytime Exploration for Multi-armed Bandits using Confidence Information}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2016},
  url = {https://proceedings.mlr.press/v48/jun16.html},
}

@inproceedings{icml2018_racing_36947,
  title = {{Racing Thompson: an Efficient Algorithm for Thompson Sampling with Non-conjugate Priors}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2018},
  url = {https://icml.cc/virtual/2018/poster/2160},
}

@inproceedings{icml2021_robust_39895,
  title = {{Robust Pure Exploration in Linear Bandits with Limited Budget}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2021},
  url = {https://icml.cc/virtual/2021/poster/9799},
}

@inproceedings{neurips2019_thresholding_59089,
  title = {{Thresholding Bandit with Optimal Aggregate Regret}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/14146},
}

@inproceedings{neurips2022_near_63809,
  title = {{Near-Optimal Collaborative Learning in Bandits}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2022},
  url = {https://nips.cc/virtual/2022/poster/54179},
}

@inproceedings{aaai2022_learning_2348,
  title = {{Learning the Optimal Recommendation from Explorative Users}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2022},
  url = {https://aaai.org/papers/09457-learning-the-optimal-recommendation-from-explorative-users/},
}

@inproceedings{icml2017_identify_36224,
  title = {{Identify the Nash Equilibrium in Static Games with Random Payoffs}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2017},
  url = {https://icml.cc/virtual/2017/poster/681},
}

@inproceedings{aaai2025_nearly_10093,
  title = {{Nearly Tight Bounds for Exploration in Streaming Multi-Armed Bandits with Known Optimality Gap}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/33956},
}

@inproceedings{icml2025_fixed_46792,
  title = {{Fixed-Confidence Multiple Change Point Identification under Bandit Feedback}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/45783},
}

@inproceedings{icml2025_the_48258,
  title = {{The Batch Complexity of Bandit Pure Exploration}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/44354},
}

@inproceedings{icml2025_near_48534,
  title = {{Near Optimal Non-asymptotic Sample Complexity of 1-Identification}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/44087},
}

@inproceedings{icml2026_variance_49497,
  title = {{Variance Driven Exploration: A Provable and Efficient Methodology for Pure Exploration in Highly Stochastic Environments}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=34cmbsgpT5},
}

@inproceedings{icml2026_online_54057,
  title = {{Online Learning with Recency: Algorithms for Sliding-window Streaming Multi-armed Bandits}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=lTqCHLllix},
}

@inproceedings{neurips2024_adaptive_70297,
  title = {{Adaptive Experimentation When You Can't Experiment}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/96795},
}

@inproceedings{neurips2024_preference_71386,
  title = {{Preference-based Pure Exploration}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/95864},
}

@inproceedings{neurips2024_enhancing_72831,
  title = {{Enhancing Preference-based Linear Bandits via Human Response Time}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/94568},
}

@inproceedings{neurips2025_frappe_79717,
  title = {{FraPPE: Fast and Efficient Preference-Based Pure Exploration}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=sJbA3xMx1B},
}

@inproceedings{iclr2026_in_86211,
  title = {{In-Context Learning for Pure Exploration}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2026},
  url = {https://openreview.net/forum?id=NFCNFvDYfE},
}

@inproceedings{iclr2026_non_89164,
  title = {{Non-Asymptotic Analysis of (Sticky) Track-and-Stop}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2026},
  url = {https://openreview.net/forum?id=vebqP5aioj},
}

@inproceedings{neurips2026_on_89985,
  title = {{On the Optimal Sample Complexity of Offline Multi-Armed Bandits with KL Regularization}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2026},
  url = {https://neurips.cc/virtual/2026/poster/155456},
}

@inproceedings{neurips2026_the_91221,
  title = {{The Sample Complexity of Multiple Change Point Identification under Bandit Feedback}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2026},
  url = {https://neurips.cc/virtual/2026/poster/152674},
}

@inproceedings{aaai2026_on_107796,
  title = {{On the Robustness of Bandit Multiple Testing}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/40148},
}

@inproceedings{icml2025_instance_48037,
  title = {{Instance-Optimal Pure Exploration for Linear Bandits on Continuous Arms}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/44570},
}

@inproceedings{icml2025_provably_48320,
  title = {{Provably Efficient Algorithm for Best Scoring Rule Identification in Online Principal-Agent Information Acquisition}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/44295},
}

@inproceedings{neurips2026_instance_90078,
  title = {{Instance-Dependent Bandit Convex Optimization in One Dimension}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2026},
  url = {https://neurips.cc/virtual/2026/poster/153738},
}

@inproceedings{neurips2026_epsilon_94929,
  title = {{\$epsilon\$-Good Action Identification in Fixed-Budget Monte Carlo Tree Search}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2026},
  url = {https://neurips.cc/virtual/2026/poster/152538},
}