% Key papers for Time series foundation models (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{aaai2021_meta_986,
  title = {{Meta-Learning Framework with Applications to Zero-Shot Time-Series Forecasting}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2021},
  url = {https://aaai.org/papers/09242-meta-learning-framework-with-applications-to-zero-shot-time-series-forecasting/},
}

@inproceedings{icml2024_moment_43922,
  title = {{MOMENT: A Family of Open Time-series Foundation Models}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/34530},
}

@inproceedings{neurips2023_forecastpfn_69739,
  title = {{ForecastPFN: Synthetically-Trained Zero-Shot Forecasting}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2023},
  url = {https://nips.cc/virtual/2023/poster/70200},
}

@inproceedings{aaai2025_federated_9175,
  title = {{Federated Foundation Models on Heterogeneous Time Series}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/33739},
}

@inproceedings{aaai2025_timepfn_11005,
  title = {{TimePFN: Effective Multivariate Time Series Forecasting with Synthetic Data}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/34288},
}

@inproceedings{neurips2024_time_71418,
  title = {{Time-FFM: Towards LM-Empowered Federated Foundation Model for Time Series Forecasting}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/95835},
}

@inproceedings{aaai2025_battling_8233,
  title = {{Battling the Non-stationarity in Time Series Forecasting via Test-time Adaptation}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/33965},
}

@inproceedings{neurips2023_improving_69929,
  title = {{Improving *day-ahead* Solar Irradiance Time Series Forecasting by Leveraging Spatio-Temporal Context}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2023},
  url = {https://nips.cc/virtual/2023/poster/70031},
}

@inproceedings{iclr2025_specialized_81676,
  title = {{Specialized Foundation Models Struggle to Beat Supervised Baselines}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/30102},
}

@inproceedings{neurips2024_brain_73332,
  title = {{Brain-JEPA: Brain Dynamics Foundation Model with Gradient Positioning and Spatiotemporal Masking}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/94113},
}

@inproceedings{aaai2026_kronos_107378,
  title = {{Kronos: A Foundation Model for the Language of Financial Markets}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/39730},
}

@inproceedings{neurips2025_ts_77050,
  title = {{TS-RAG: Retrieval-Augmented Generation based Time Series Foundation Models are Stronger Zero-Shot Forecaster}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=PymOnHw4Ty},
}

@inproceedings{icml2025_visionts_46118,
  title = {{VisionTS: Visual Masked Autoencoders Are Free-Lunch Zero-Shot Time Series Forecasters}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/46441},
}

@inproceedings{aaai2026_deepsensemoe_99869,
  title = {{DeepSenseMoE: Harnessing Power of Time Series Foundation Models for Few-Shot Human Activity Recognition}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/36990},
}

@inproceedings{icml2025_sundial_46992,
  title = {{Sundial: A Family of Highly Capable Time Series Foundation Models}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/45591},
}

@inproceedings{neurips2025_this_74842,
  title = {{This Time is Different: An Observability Perspective on Time Series Foundation Models}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=1jDAYXfcS2},
}

@inproceedings{neurips2025_sempo_77895,
  title = {{SEMPO: Lightweight Foundation Models for Time Series Forecasting}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=YngHXbJM8g},
}

@inproceedings{iclr2025_towards_83828,
  title = {{Towards Neural Scaling Laws for Time Series Foundation Models}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/27992},
}

@inproceedings{aaai2026_a_107222,
  title = {{A Unified Shape-Aware Foundation Model for Time Series Classification}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/39574},
}

@inproceedings{icml2025_moirai_47391,
  title = {{Moirai-MoE: Empowering Time Series Foundation Models with Sparse Mixture of Experts}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/45201},
}

@inproceedings{neurips2025_multi_76915,
  title = {{Multi-Scale Finetuning for Encoder-based Time Series Foundation Models}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=OPOBV0zXu7},
}

@inproceedings{neurips2025_less_78943,
  title = {{Less is More: Unlocking Specialization of Time Series Foundation Models via Structured Pruning}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=jy4bBsr1Jc},
}

@inproceedings{neurips2025_synthetic_80200,
  title = {{Synthetic Series-Symbol Data Generation for Time Series Foundation Models}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=xB1ZNgq0Xp},
}