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

@inproceedings{iclr2019_diversity_29046,
  title = {{Diversity is All You Need: Learning Skills without a Reward Function}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2019},
  url = {https://iclr.cc/virtual/2019/poster/720},
}

@inproceedings{iclr2019_composing_29219,
  title = {{Composing Complex Skills by Learning Transition Policies}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2019},
  url = {https://iclr.cc/virtual/2019/poster/792},
}

@inproceedings{icml2020_explore_38186,
  title = {{Explore, Discover and Learn: Unsupervised Discovery of State-Covering Skills}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2020},
  url = {https://icml.cc/virtual/2020/poster/6014},
}

@inproceedings{icml2021_aps_39001,
  title = {{APS: Active Pretraining with Successor Features}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2021},
  url = {https://icml.cc/virtual/2021/poster/9241},
}

@inproceedings{neurips2021_urlb_63083,
  title = {{URLB: Unsupervised Reinforcement Learning Benchmark}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2021},
  url = {https://openreview.net/forum?id=lwrPkQP_is},
}

@inproceedings{aaai2022_unsupervised_2922,
  title = {{Unsupervised Reinforcement Learning in Multiple Environments}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2022},
  url = {https://aaai.org/papers/07850-unsupervised-reinforcement-learning-in-multiple-environments/},
}

@inproceedings{aaai2022_wasserstein_2942,
  title = {{Wasserstein Unsupervised Reinforcement Learning}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2022},
  url = {https://aaai.org/papers/06884-wasserstein-unsupervised-reinforcement-learning/},
}

@inproceedings{iclr2022_lipschitz_30984,
  title = {{Lipschitz-constrained Unsupervised Skill Discovery}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2022},
  url = {https://iclr.cc/virtual/2022/poster/6488},
}

@inproceedings{icml2023_controllability_41816,
  title = {{Controllability-Aware Unsupervised Skill Discovery}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2023},
  url = {https://icml.cc/virtual/2023/poster/24770},
}

@inproceedings{iclr2022_learning_31477,
  title = {{Learning more skills through optimistic exploration}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2022},
  url = {https://iclr.cc/virtual/2022/poster/6475},
}

@inproceedings{iclr2023_choreographer_32541,
  title = {{Choreographer: Learning and Adapting Skills in Imagination}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2023},
  url = {https://iclr.cc/virtual/2023/poster/11101},
}

@inproceedings{neurips2024_disentangled_73161,
  title = {{Disentangled Unsupervised Skill Discovery for Efficient Hierarchical Reinforcement Learning}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/94271},
}

@inproceedings{icml2023_behavior_41740,
  title = {{Behavior Contrastive Learning for Unsupervised Skill Discovery}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2023},
  url = {https://icml.cc/virtual/2023/poster/24390},
}

@inproceedings{neurips2021_unsupervised_63383,
  title = {{Unsupervised Domain Adaptation with Dynamics-Aware Rewards in Reinforcement Learning}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2021},
  url = {https://nips.cc/virtual/2021/poster/27766},
}

@inproceedings{neurips2022_open_64746,
  title = {{Open-Ended Reinforcement Learning with Neural Reward Functions}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2022},
  url = {https://nips.cc/virtual/2022/poster/55000},
}

@inproceedings{iclr2022_the_30846,
  title = {{The Information Geometry of Unsupervised Reinforcement Learning}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2022},
  url = {https://iclr.cc/virtual/2022/poster/6206},
}

@inproceedings{iclr2024_metra_34765,
  title = {{METRA: Scalable Unsupervised RL with Metric-Aware Abstraction}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/18309},
}

@inproceedings{neurips2022_a_64795,
  title = {{A Mixture Of Surprises for Unsupervised Reinforcement Learning}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2022},
  url = {https://nips.cc/virtual/2022/poster/55181},
}

@inproceedings{neurips2024_subwords_72553,
  title = {{Subwords as Skills: Tokenization for Sparse-Reward Reinforcement Learning}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/94819},
}

@inproceedings{iclr2023_euclid_33381,
  title = {{EUCLID: Towards Efficient Unsupervised Reinforcement Learning with Multi-choice Dynamics Model}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2023},
  url = {https://iclr.cc/virtual/2023/poster/11688},
}

@inproceedings{neurips2024_do_70682,
  title = {{Do's and Don'ts: Learning Desirable Skills with Instruction Videos}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/96441},
}

@inproceedings{aaai2025_skill_10777,
  title = {{Skill Disentanglement in Reproducing Kernel Hilbert Space}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/33774},
}

@inproceedings{iclr2024_task_35691,
  title = {{Task Adaptation from Skills: Information Geometry, Disentanglement, and New Objectives for Unsupervised Reinforcement Learning}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/17382},
}

@inproceedings{icml2024_constrained_43682,
  title = {{Constrained Ensemble Exploration for Unsupervised Skill Discovery}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/34770},
}

@inproceedings{icml2025_efficient_46094,
  title = {{Efficient Skill Discovery via Regret-Aware Optimization}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/46465},
}

@inproceedings{icml2025_leveraging_48634,
  title = {{Leveraging Skills from Unlabeled Prior Data for Efficient Online Exploration}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/43987},
}

@inproceedings{icml2026_unsupervised_52524,
  title = {{Unsupervised Hierarchical Skill Discovery}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=Wrywrky3Fk},
}

@inproceedings{icml2026_learning_54600,
  title = {{Learning Generalizable Skill Policy with Data-Efficient Unsupervised RL}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=qgAKuqzYBC},
}

@inproceedings{neurips2024_peac_71731,
  title = {{PEAC: Unsupervised Pre-training for Cross-Embodiment Reinforcement Learning}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/95555},
}

@inproceedings{neurips2024_skild_73433,
  title = {{SkiLD: Unsupervised Skill Discovery Guided by Factor Interactions}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/94028},
}

@inproceedings{neurips2024_exploration_73920,
  title = {{Exploration by Learning Diverse Skills through Successor State Representations}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/93591},
}

@inproceedings{iclr2026_susd_85796,
  title = {{SUSD: Structured Unsupervised Skill Discovery through State Factorization}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2026},
  url = {https://openreview.net/forum?id=INr5TSooxR},
}

@inproceedings{iclr2026_exploratory_88177,
  title = {{Exploratory Diffusion Model for Unsupervised Reinforcement Learning}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2026},
  url = {https://openreview.net/forum?id=k0Kb1ynFbt},
}

@inproceedings{neurips2026_unifying_91269,
  title = {{Unifying Goal-Conditioned RL and Unsupervised Skill Learning via Control-Maximization}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2026},
  url = {https://neurips.cc/virtual/2026/poster/153300},
}

@inproceedings{aaai2026_beyond_106906,
  title = {{Beyond Fixed Tasks: Unsupervised Environment Design for Task-Level Pairs}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/39258},
}

@inproceedings{aaai2026_discovering_107254,
  title = {{Discovering Mixture Skills for Unsupervised Reinforcement Learning}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/39606},
}

@inproceedings{neurips2025_periodic_75734,
  title = {{Periodic Skill Discovery}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=BPSU46emit},
}