% Key papers for Structure-based molecule design with diffusion (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{aaai2019_learning_101722,
  title = {{Learning Vine Copula Models for Synthetic Data Generation}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2019},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/4437},
}

@inproceedings{iclr2024_deep_34552,
  title = {{Deep Confident Steps to New Pockets: Strategies for Docking Generalization}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/18522},
}

@inproceedings{icml2023_decompdiff_41722,
  title = {{DecompDiff: Diffusion Models with Decomposed Priors for Structure-Based Drug Design}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2023},
  url = {https://icml.cc/virtual/2023/poster/23697},
}

@inproceedings{cvpr2021_mol2image_17423,
  title = {{Mol2Image: Improved Conditional Flow Models for Molecule to Image Synthesis}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2021},
}

@inproceedings{aaai2024_a_5042,
  title = {{A Multi-Modal Contrastive Diffusion Model for Therapeutic Peptide Generation}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/27749},
}

@inproceedings{aaai2024_text_7531,
  title = {{Text-Guided Molecule Generation with Diffusion Language Model}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/27761},
}

@inproceedings{aaai2024_binding_5300,
  title = {{Binding-Adaptive Diffusion Models for Structure-Based Drug Design}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29162},
}

@inproceedings{neurips2023_functional_69304,
  title = {{Functional-Group-Based Diffusion for Pocket-Specific Molecule Generation and Elaboration}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2023},
  url = {https://nips.cc/virtual/2023/poster/70596},
}

@inproceedings{icml2025_diffms_46653,
  title = {{DiffMS: Diffusion Generation of Molecules Conditioned on Mass Spectra}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/45918},
}

@inproceedings{iclr2024_decompopt_34638,
  title = {{DecompOpt: Controllable and Decomposed Diffusion Models for Structure-based Molecular Optimization}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/18436},
}

@inproceedings{iclr2023_retrieval_33335,
  title = {{Retrieval-based Controllable Molecule Generation}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2023},
  url = {https://iclr.cc/virtual/2023/poster/11781},
}

@inproceedings{icml2023_exploring_42430,
  title = {{Exploring Chemical Space with Score-based Out-of-distribution Generation}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2023},
  url = {https://icml.cc/virtual/2023/poster/25071},
}

@inproceedings{icml2025_genmol_46933,
  title = {{GenMol: A Drug Discovery Generalist with Discrete Diffusion}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/45647},
}

@inproceedings{icml2025_ldmol_48396,
  title = {{LDMol: A Text-to-Molecule Diffusion Model with Structurally Informative Latent Space Surpasses AR Models}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/44220},
}

@inproceedings{iclr2025_unigem_81793,
  title = {{UniGEM: A Unified Approach to Generation and Property Prediction for Molecules}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/29987},
}

@inproceedings{icml2024_rethinking_43607,
  title = {{Rethinking Specificity in SBDD: Leveraging Delta Score and Energy-Guided Diffusion}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/34845},
}

@inproceedings{neurips2024_molecule_70494,
  title = {{Molecule Generation with Fragment Retrieval Augmentation}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/96613},
}

@inproceedings{icml2024_preference_45363,
  title = {{Preference Optimization for Molecule Synthesis with Conditional Residual Energy-based Models}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/33088},
}

@inproceedings{neurips2024_reprogramming_72667,
  title = {{Reprogramming Pretrained Target-Specific Diffusion Models for Dual-Target Drug Design}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/94717},
}

@inproceedings{iclr2025_fragment_83344,
  title = {{Fragment and Geometry Aware Tokenization of Molecules for Structure-Based Drug Design Using Language Models}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/28470},
}

@inproceedings{iclr2026_graph_88302,
  title = {{Graph Diffusion Transformers are In-Context Molecular Designers}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2026},
  url = {https://openreview.net/forum?id=lJ87GN5zJc},
}

@inproceedings{aaai2026_de_100023,
  title = {{De Novo Molecular Generation from Mass Spectra via Many-Body Enhanced Diffusion}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/37074},
}

@inproceedings{aaai2026_apo2mol_100087,
  title = {{Apo2Mol: 3D Molecule Generation via Dynamic Pocket-Aware Diffusion Models}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/37138},
}

@inproceedings{aaai2026_hierarchical_106893,
  title = {{Hierarchical Structure-Property Alignment for Data-Efficient Molecular Generation and Editing}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/39245},
}

@inproceedings{aaai2026_disturbance_106937,
  title = {{Disturbance-based Discretization, Differentiable IDS Channel, and an IDS-Correcting Code for DNA-based Storage}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/39289},
}

@inproceedings{aaai2026_pepccd_107701,
  title = {{PepCCD: A Contrastive Conditioned Diffusion Framework for Target-Specific Peptide Generation}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/40053},
}