% Key papers for Task-inference meta-RL (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{icml2019_efficient_37327,
  title = {{Efficient Off-Policy Meta-Reinforcement Learning via Probabilistic Context Variables}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2019},
  url = {https://icml.cc/virtual/2019/poster/3641},
}

@inproceedings{neurips2018_meta_57372,
  title = {{Meta-Reinforcement Learning of Structured Exploration Strategies}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/11518},
}

@inproceedings{iclr2020_improving_29583,
  title = {{Improving Generalization in Meta Reinforcement Learning using Learned Objectives}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2020},
  url = {https://openreview.net/forum?id=S1evHerYPr},
}

@inproceedings{aaai2020_reinforcement_102211,
  title = {{Reinforcement Learning Based Meta-Path Discovery in Large-Scale Heterogeneous Information Networks}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2020},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/6073},
}

@inproceedings{neurips2019_guided_58359,
  title = {{Guided Meta-Policy Search}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/14577},
}

@inproceedings{aaai2022_adapt_1706,
  title = {{Adapt to Environment Sudden Changes by Learning a Context Sensitive Policy}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2022},
  url = {https://aaai.org/papers/07637-adapt-to-environment-sudden-changes-by-learning-a-context-sensitive-policy/},
}

@inproceedings{aaai2021_towards_1528,
  title = {{Towards Effective Context for Meta-Reinforcement Learning: an Approach based on Contrastive Learning}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2021},
  url = {https://aaai.org/papers/07457-towards-effective-context-for-meta-reinforcement-learning-an-approach-based-on-contrastive-learning/},
}

@inproceedings{iclr2020_meta_29611,
  title = {{Meta-Q-Learning}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2020},
  url = {https://openreview.net/forum?id=SJeD3CEFPH},
}

@inproceedings{iclr2020_reinforcement_29913,
  title = {{Reinforcement Learning with Competitive Ensembles of Information-Constrained Primitives}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2020},
  url = {https://openreview.net/forum?id=ryxgJTEYDr},
}

@inproceedings{aaai2019_meta_103486,
  title = {{Meta Learning for Image Captioning}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2019},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/4883},
}

@inproceedings{iclr2021_evolving_29952,
  title = {{Evolving Reinforcement Learning Algorithms}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2021},
  url = {https://iclr.cc/virtual/2021/poster/3056},
}

@inproceedings{neurips2022_on_65924,
  title = {{On the Effectiveness of Fine-tuning Versus Meta-reinforcement Learning}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2022},
  url = {https://nips.cc/virtual/2022/poster/52865},
}

@inproceedings{aaai2022_introducing_2264,
  title = {{Introducing Symmetries to Black Box Meta Reinforcement Learning}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2022},
  url = {https://aaai.org/papers/07202-introducing-symmetries-to-black-box-meta-reinforcement-learning/},
}

@inproceedings{neurips2022_discovered_65432,
  title = {{Discovered Policy Optimisation}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2022},
  url = {https://nips.cc/virtual/2022/poster/53272},
}

@inproceedings{iclr2020_meta_29375,
  title = {{Meta-learning curiosity algorithms}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2020},
  url = {https://openreview.net/forum?id=BygdyxHFDS},
}

@inproceedings{aaai2023_meta_4144,
  title = {{Meta-Reinforcement Learning Based on Self-Supervised Task Representation Learning}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2023},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/26210},
}

@inproceedings{iclr2022_skill_31604,
  title = {{Skill-based Meta-Reinforcement Learning}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2022},
  url = {https://iclr.cc/virtual/2022/poster/6702},
}

@inproceedings{icml2021_metacure_39610,
  title = {{MetaCURE: Meta Reinforcement Learning with Empowerment-Driven Exploration}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2021},
  url = {https://icml.cc/virtual/2021/poster/9825},
}

@inproceedings{iclr2019_promp_29079,
  title = {{ProMP: Proximal Meta-Policy Search}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2019},
  url = {https://iclr.cc/virtual/2019/poster/788},
}

@inproceedings{icml2021_decoupling_39209,
  title = {{Decoupling Exploration and Exploitation for Meta-Reinforcement Learning without Sacrifices}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2021},
  url = {https://icml.cc/virtual/2021/poster/8991},
}

@inproceedings{aaai2024_meta_6631,
  title = {{Meta-Reinforcement Learning via Exploratory Task Clustering}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29046},
}

@inproceedings{neurips2024_towards_72077,
  title = {{Towards an Information Theoretic Framework of Context-Based Offline Meta-Reinforcement Learning}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/95247},
}

@inproceedings{neurips2024_meta_72363,
  title = {{Meta-DT: Offline Meta-RL as Conditional Sequence Modeling with World Model Disentanglement}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/94988},
}

@inproceedings{neurips2025_meta_74832,
  title = {{Meta-World+: An Improved, Standardized, RL Benchmark}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=1de3azE606},
}

@inproceedings{aaai2024_metacard_6632,
  title = {{MetaCARD: Meta-Reinforcement Learning with Task Uncertainty Feedback via Decoupled Context-Aware Reward and Dynamics Components}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29482},
}

@inproceedings{aaai2024_constrained_5478,
  title = {{Constrained Meta-Reinforcement Learning for Adaptable Safety Guarantee with Differentiable Convex Programming}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/30088},
}

@inproceedings{aaai2024_decoupling_5631,
  title = {{Decoupling Meta-Reinforcement Learning with Gaussian Task Contexts and Skills}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29127},
}

@inproceedings{iclr2024_mamba_33486,
  title = {{MAMBA: an Effective World Model Approach for Meta-Reinforcement Learning}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/19589},
}

@inproceedings{neurips2024_first_70966,
  title = {{First-Explore, then Exploit: Meta-Learning to Solve Hard Exploration-Exploitation Trade-Offs}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/96238},
}

@inproceedings{neurips2024_skill_71383,
  title = {{Skill-aware Mutual Information Optimisation for Zero-shot Generalisation in Reinforcement Learning}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/95867},
}

@inproceedings{neurips2024_amago_71938,
  title = {{AMAGO-2: Breaking the Multi-Task Barrier in Meta-Reinforcement Learning with Transformers}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/95369},
}

@inproceedings{neurips2024_can_72702,
  title = {{Can Learned Optimization Make Reinforcement Learning Less Difficult?}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/94685},
}

@inproceedings{neurips2024_meta_74125,
  title = {{Meta-Reinforcement Learning with Universal Policy Adaptation: Provable Near-Optimality under All-task Optimum Comparator}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/93412},
}

@inproceedings{neurips2025_text_75593,
  title = {{Text-to-Decision Agent: Offline Meta-Reinforcement Learning from Natural Language Supervision}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=9qCejdqPXa},
}

@inproceedings{iclr2024_discovering_34244,
  title = {{Discovering Temporally-Aware Reinforcement Learning Algorithms}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/18831},
}

@inproceedings{iclr2025_learning_80830,
  title = {{Learning Task Belief Similarity with Latent Dynamics for Meta-Reinforcement Learning}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/30938},
}

@inproceedings{iclr2025_distilling_81211,
  title = {{Distilling Reinforcement Learning Algorithms for In-Context Model-Based Planning}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/30559},
}

@inproceedings{iclr2026_self_87841,
  title = {{Self-Improving Skill Learning for Robust Skill-based Meta-Reinforcement Learning}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2026},
  url = {https://openreview.net/forum?id=g6MncErbEb},
}

@inproceedings{aaai2026_improving_106961,
  title = {{Improving Generalization in Offline Meta-Reinforcement Learning via Cross-task Contexts}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/39313},
}

@inproceedings{icml2026_counterfactual_53098,
  title = {{Counterfactual Bootstrap for Robust Meta-Reinforcement Learning}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=c4abksRFwY},
}