% Key papers for Subgoal generation for hierarchical RL (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{neurips2018_data_56994,
  title = {{Data-Efficient Hierarchical Reinforcement Learning}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/11333},
}

@inproceedings{neurips2019_language_58455,
  title = {{Language as an Abstraction for Hierarchical Deep Reinforcement Learning}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/13979},
}

@inproceedings{icml2018_self_36979,
  title = {{Self-Consistent Trajectory Autoencoder: Hierarchical Reinforcement Learning with Trajectory Embeddings}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2018},
  url = {https://icml.cc/virtual/2018/poster/2337},
}

@inproceedings{iclr2019_near_28863,
  title = {{Near-Optimal Representation Learning for Hierarchical Reinforcement Learning}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2019},
  url = {https://iclr.cc/virtual/2019/poster/713},
}

@inproceedings{neurips2020_generating_59938,
  title = {{Generating Adjacency-Constrained Subgoals in Hierarchical Reinforcement Learning}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/17836},
}

@inproceedings{iclr2021_hierarchical_30660,
  title = {{Hierarchical Reinforcement Learning by Discovering Intrinsic Options}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2021},
  url = {https://iclr.cc/virtual/2021/poster/2805},
}

@inproceedings{neurips2021_landmark_61864,
  title = {{Landmark-Guided Subgoal Generation in Hierarchical Reinforcement Learning}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2021},
  url = {https://nips.cc/virtual/2021/poster/28220},
}

@inproceedings{aaai2019_diversity_101715,
  title = {{Diversity-Driven Extensible Hierarchical Reinforcement Learning}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2019},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/4430},
}

@inproceedings{iclr2021_learning_30745,
  title = {{Learning Subgoal Representations with Slow Dynamics}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2021},
  url = {https://iclr.cc/virtual/2021/poster/3356},
}

@inproceedings{neurips2022_deep_66364,
  title = {{Deep Hierarchical Planning from Pixels}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2022},
  url = {https://nips.cc/virtual/2022/poster/54941},
}

@inproceedings{neurips2020_counterfactual_59613,
  title = {{Counterfactual Data Augmentation using Locally Factored Dynamics}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/18725},
}

@inproceedings{neurips2021_hierarchical_61497,
  title = {{Hierarchical Reinforcement Learning with Timed Subgoals}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2021},
  url = {https://nips.cc/virtual/2021/poster/27318},
}

@inproceedings{aaai2023_state_4727,
  title = {{State-Conditioned Adversarial Subgoal Generation}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2023},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/26213},
}

@inproceedings{iclr2022_active_31745,
  title = {{Active Hierarchical Exploration with Stable Subgoal Representation Learning}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2022},
  url = {https://iclr.cc/virtual/2022/poster/6965},
}

@inproceedings{aaai2024_handling_6186,
  title = {{Handling Long and Richly Constrained Tasks through Constrained Hierarchical Reinforcement Learning}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/30132},
}

@inproceedings{neurips2023_cqm_69743,
  title = {{CQM: Curriculum Reinforcement Learning with a Quantized World Model}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2023},
  url = {https://nips.cc/virtual/2023/poster/70196},
}

@inproceedings{neurips2024_a_70392,
  title = {{A theoretical case-study of Scalable Oversight in Hierarchical Reinforcement Learning}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/96710},
}

@inproceedings{neurips2025_state_76162,
  title = {{State-Covering Trajectory Stitching for Diffusion Planners}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=GEzd5K5s5u},
}

@inproceedings{iclr2024_reconciling_35263,
  title = {{Reconciling Spatial and Temporal Abstractions for Goal Representation}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/17810},
}

@inproceedings{icml2024_probabilistic_44797,
  title = {{Probabilistic Subgoal Representations for Hierarchical Reinforcement Learning}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/33655},
}

@inproceedings{icml2024_piper_45227,
  title = {{PIPER: Primitive-Informed Preference-based Hierarchical Reinforcement Learning via Hindsight Relabeling}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/33225},
}

@inproceedings{icml2025_hierarchical_45912,
  title = {{Hierarchical Reinforcement Learning with Uncertainty-Guided Diffusional Subgoals}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/46632},
}

@inproceedings{icml2025_graph_46215,
  title = {{Graph-Assisted Stitching for Offline Hierarchical Reinforcement Learning}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/46345},
}

@inproceedings{icml2025_hierarchical_48087,
  title = {{Hierarchical Reinforcement Learning with Targeted Causal Interventions}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/44521},
}

@inproceedings{icml2026_chain_49689,
  title = {{Chain-of-Goals Hierarchical Policy for Long-Horizon Offline Goal-Conditioned RL}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=4nfItZvfna},
}

@inproceedings{icml2026_laplacian_49849,
  title = {{Laplacian Representations for Decision-Time Planning}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=6JwkAlGLjT},
}

@inproceedings{neurips2025_normalizing_75980,
  title = {{Normalizing Flows are Capable Models for Continuous Control}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=EJ34X5VWwu},
}

@inproceedings{neurips2025_1000_79691,
  title = {{1000 Layer Networks for Self-Supervised RL: Scaling Depth Can Enable New Goal-Reaching Capabilities}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=s0JVsx3bx1},
}

@inproceedings{iclr2025_overcoming_83947,
  title = {{Overcoming Slow Decision Frequencies in Continuous Control: Model-Based Sequence Reinforcement Learning for Model-Free Control}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/27877},
}

@inproceedings{iclr2026_hierarchical_86772,
  title = {{Hierarchical Entity-centric Reinforcement Learning with Factored Subgoal Diffusion}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2026},
  url = {https://openreview.net/forum?id=TimC6hxVHj},
}

@inproceedings{iclr2026_strict_87516,
  title = {{Strict Subgoal Execution: Reliable Long-Horizon Planning in Hierarchical Reinforcement Learning}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2026},
  url = {https://openreview.net/forum?id=cMpOvMuyYa},
}

@inproceedings{aaai2026_enhancing_107724,
  title = {{Enhancing Exploration and Exploitation in Hierarchical Reinforcement Learning with Subgoal Graph Learning}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/40076},
}

@inproceedings{iclr2025_discrete_81762,
  title = {{Discrete Latent Plans via Semantic Skill Abstractions}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/30017},
}

@inproceedings{iclr2026_rd_84664,
  title = {{RD-HRL: Generating Reliable Sub-Goals for Long-Horizon Sparse-Reward Tasks}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2026},
  url = {https://openreview.net/forum?id=5E5sd3TWGD},
}