% Key papers for Skill learning and diffusion policies (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{neurips2017_hindsight_56364,
  title = {{Hindsight Experience Replay}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2017},
  url = {https://nips.cc/virtual/2017/poster/9281},
}

@inproceedings{iclr2018_learning_28684,
  title = {{Learning an Embedding Space for Transferable Robot Skills}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2018},
  url = {https://iclr.cc/virtual/2018/poster/6},
}

@inproceedings{aaai2025_deep_8679,
  title = {{Deep Reinforcement Learning for Robotics: A Survey of Real-World Successes}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/35095},
}

@inproceedings{cvpr2020_rl_16083,
  title = {{RL-CycleGAN: Reinforcement Learning Aware Simulation-to-Real}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2020},
}

@inproceedings{aaai2017_grounded_103407,
  title = {{Grounded Action Transformation for Robot Learning in Simulation}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2017},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/11044},
}

@inproceedings{iclr2021_self_30628,
  title = {{Self-Supervised Policy Adaptation during Deployment}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2021},
  url = {https://iclr.cc/virtual/2021/poster/2761},
}

@inproceedings{iclr2019_policy_28871,
  title = {{Policy Transfer with Strategy Optimization}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2019},
  url = {https://iclr.cc/virtual/2019/poster/918},
}

@inproceedings{icml2020_one_38563,
  title = {{One Policy to Control Them All: Shared Modular Policies for Agent-Agnostic Control}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2020},
  url = {https://icml.cc/virtual/2020/poster/6549},
}

@inproceedings{iclr2021_parrot_30414,
  title = {{Parrot: Data-Driven Behavioral Priors for Reinforcement Learning}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2021},
  url = {https://iclr.cc/virtual/2021/poster/2862},
}

@inproceedings{icml2018_taco_37027,
  title = {{TACO: Learning Task Decomposition via Temporal Alignment for Control}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2018},
  url = {https://icml.cc/virtual/2018/poster/2465},
}

@inproceedings{iclr2017_generalizing_28384,
  title = {{Generalizing Skills with Semi-Supervised Reinforcement Learning}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2017},
  url = {https://openreview.net/forum?id=ryHlUtqge},
}

@inproceedings{aaai2021_encoding_518,
  title = {{Encoding Human Domain Knowledge to Warm Start Reinforcement Learning}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2021},
  url = {https://aaai.org/papers/05042-encoding-human-domain-knowledge-to-warm-start-reinforcement-learning/},
}

@inproceedings{neurips2018_hardware_57196,
  title = {{Hardware Conditioned Policies for Multi-Robot Transfer Learning}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/11889},
}

@inproceedings{cvpr2024_spoc_24725,
  title = {{SPOC: Imitating Shortest Paths in Simulation Enables Effective Navigation and Manipulation in the Real World}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/30192},
}

@inproceedings{iclr2020_the_29772,
  title = {{The Ingredients of Real World Robotic Reinforcement Learning}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2020},
  url = {https://openreview.net/forum?id=rJe2syrtvS},
}

@inproceedings{neurips2017_towards_56733,
  title = {{Towards Generalization and Simplicity in Continuous Control}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2017},
  url = {https://nips.cc/virtual/2017/poster/9424},
}

@inproceedings{iclr2018_progressive_28395,
  title = {{Progressive Reinforcement Learning with Distillation for Multi-Skilled Motion Control}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2018},
  url = {https://iclr.cc/virtual/2018/poster/300},
}

@inproceedings{iclr2022_accelerated_31412,
  title = {{Accelerated Policy Learning with Parallel Differentiable Simulation}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2022},
  url = {https://iclr.cc/virtual/2022/poster/6923},
}

@inproceedings{iclr2020_composing_29407,
  title = {{Composing Task-Agnostic Policies with Deep Reinforcement Learning}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2020},
  url = {https://openreview.net/forum?id=H1ezFREtwH},
}

@inproceedings{icml2020_a_37877,
  title = {{A Natural Lottery Ticket Winner: Reinforcement Learning with Ordinary Neural Circuits}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2020},
  url = {https://icml.cc/virtual/2020/poster/6144},
}

@inproceedings{aaai2025_skilltree_10778,
  title = {{SkillTree: Explainable Skill-Based Deep Reinforcement Learning for Long-Horizon Control Tasks}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/35451},
}

@inproceedings{neurips2024_efficient_70389,
  title = {{Efficient Multi-task Reinforcement Learning with Cross-Task Policy Guidance}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/96712},
}

@inproceedings{aaai2025_differentiable_8733,
  title = {{Differentiable Information Enhanced Model-Based Reinforcement Learning}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/34419},
}

@inproceedings{iclr2024_domain_34050,
  title = {{Domain Randomization via Entropy Maximization}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/19025},
}

@inproceedings{aaai2024_sim_7337,
  title = {{Sim-to-Lab-to-Real: Safe Reinforcement Learning with Shielding and Generalization Guarantees (Abstract Reprint)}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/30599},
}

@inproceedings{aaai2025_efficient_8911,
  title = {{Efficient Language-instructed Skill Acquisition via Reward-Policy Co-Evolution}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/33597},
}

@inproceedings{aaai2025_evolutionary_9039,
  title = {{Evolutionary Reinforcement Learning with Parameterized Action Primitives for Diverse Manipulation Tasks}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/33606},
}

@inproceedings{aaai2025_in_9543,
  title = {{In-Context Policy Adaptation via Cross-Domain Skill Diffusion}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/34373},
}

@inproceedings{icml2025_mentor_48829,
  title = {{MENTOR: Mixture-of-Experts Network with Task-Oriented Perturbation for Visual Reinforcement Learning}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/43793},
}

@inproceedings{neurips2024_llm_72373,
  title = {{LLM-based Skill Diffusion for Zero-shot Policy Adaptation}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/94979},
}

@inproceedings{neurips2024_make_73947,
  title = {{Make-An-Agent: A Generalizable Policy Network Generator with Behavior-Prompted Diffusion}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/93565},
}

@inproceedings{neurips2025_dynaguide_77768,
  title = {{DynaGuide: Steering Diffusion Polices with Active Dynamic Guidance}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=XOw7Yf8qN3},
}

@inproceedings{neurips2025_conditioning_79433,
  title = {{Conditioning Matters: Training Diffusion Policies is Faster Than You Think}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=pKQcmLHoGG},
}

@inproceedings{iclr2024_drs_33676,
  title = {{DrS: Learning Reusable Dense Rewards for Multi-Stage Tasks}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/19399},
}

@inproceedings{iclr2024_robot_34106,
  title = {{Robot Fleet Learning via Policy Merging}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/18969},
}

@inproceedings{iclr2024_time_35161,
  title = {{Time-Varying Propensity Score to Bridge the Gap between the Past and Present}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/17912},
}

@inproceedings{icml2024_prise_45391,
  title = {{PRISE: LLM-Style Sequence Compression for Learning Temporal Action Abstractions in Control}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/33060},
}

@inproceedings{icml2025_flow_46322,
  title = {{Flow-based Domain Randomization for Learning and Sequencing Robotic Skills}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/46239},
}