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

@inproceedings{icml2020_a_37874,
  title = {{A Graph to Graphs Framework for Retrosynthesis Prediction}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2020},
  url = {https://icml.cc/virtual/2020/poster/6449},
}

@inproceedings{neurips2021_learning_62283,
  title = {{Learning Graph Models for Retrosynthesis Prediction}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2021},
  url = {https://nips.cc/virtual/2021/poster/26085},
}

@inproceedings{aaai2021_gta_651,
  title = {{GTA: Graph Truncated Attention for Retrosynthesis}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2021},
  url = {https://aaai.org/papers/00531-gta-graph-truncated-attention-for-retrosynthesis/},
}

@inproceedings{neurips2020_retroxpert_60717,
  title = {{RetroXpert: Decompose Retrosynthesis Prediction Like A Chemist}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/16855},
}

@inproceedings{neurips2021_towards_63554,
  title = {{Towards understanding retrosynthesis by energy-based models}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2021},
  url = {https://nips.cc/virtual/2021/poster/28559},
}

@inproceedings{aaai2025_gdiffretro_9270,
  title = {{GDiffRetro: Retrosynthesis Prediction with Dual Graph Enhanced Molecular Representation and Diffusion Generation}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/33373},
}

@inproceedings{aaai2025_advancing_8057,
  title = {{Advancing Retrosynthesis with Retrieval-Augmented Graph Generation}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/34203},
}

@inproceedings{aaai2026_trace_99850,
  title = {{TRACE: Transformation-Aware Graph Refinement for Reaction Condition Prediction}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/36971},
}

@inproceedings{iclr2023_matching_33215,
  title = {{Matching receptor to odorant with protein language and graph neural networks}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2023},
  url = {https://iclr.cc/virtual/2023/poster/11500},
}

@inproceedings{neurips2026_matching_95065,
  title = {{Matching-while-Decoding: Enhancing Template-Free Retrosynthesis via Explicit Structural Alignment}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2026},
  url = {https://neurips.cc/virtual/2026/poster/148852},
}