% Key papers for Protein fitness and variant effect prediction (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{neurips2021_language_63397,
  title = {{Language models enable zero-shot prediction of the effects of mutations on protein function}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2021},
  url = {https://nips.cc/virtual/2021/poster/26354},
}

@inproceedings{neurips2021_flip_63187,
  title = {{FLIP: Benchmark tasks in fitness landscape inference for proteins}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2021},
  url = {https://openreview.net/forum?id=p2dMLEwL8tF},
}

@inproceedings{icml2022_tranception_41286,
  title = {{Tranception: Protein Fitness Prediction with Autoregressive Transformers and Inference-time Retrieval}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2022},
  url = {https://icml.cc/virtual/2022/poster/18181},
}

@inproceedings{icml2022_de_40411,
  title = {{De novo mass spectrometry peptide sequencing with a transformer model}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2022},
  url = {https://icml.cc/virtual/2022/poster/16795},
}

@inproceedings{neurips2023_proteingym_68296,
  title = {{ProteinGym: Large-Scale Benchmarks for Protein Fitness Prediction and Design}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2023},
  url = {https://nips.cc/virtual/2023/poster/73578},
}

@inproceedings{iclr2025_protein_82348,
  title = {{Protein Language Model Fitness is a Matter of Preference}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/29443},
}

@inproceedings{neurips2023_proteinnpt_67195,
  title = {{ProteinNPT: Improving Protein Property Prediction and Design with Non-Parametric Transformers}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2023},
  url = {https://nips.cc/virtual/2023/poster/72519},
}

@inproceedings{iclr2025_iggm_84178,
  title = {{IgGM: A Generative Model for Functional Antibody and Nanobody Design}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/27650},
}

@inproceedings{icml2022_biological_40288,
  title = {{Biological Sequence Design with GFlowNets}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2022},
  url = {https://icml.cc/virtual/2022/poster/17337},
}

@inproceedings{neurips2022_non_64313,
  title = {{Non-identifiability and the Blessings of Misspecification in Models of Molecular Fitness}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2022},
  url = {https://nips.cc/virtual/2022/poster/53815},
}

@inproceedings{neurips2023_predicting_68534,
  title = {{Predicting a Protein's Stability under a Million Mutations}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2023},
  url = {https://nips.cc/virtual/2023/poster/71293},
}

@inproceedings{neurips2023_openproteinset_69020,
  title = {{OpenProteinSet: Training data for structural biology at scale}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2023},
  url = {https://nips.cc/virtual/2023/poster/73507},
}

@inproceedings{icml2023_end_43209,
  title = {{End-to-End Full-Atom Antibody Design}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2023},
  url = {https://icml.cc/virtual/2023/poster/24962},
}

@inproceedings{iclr2024_mape_35028,
  title = {{MAPE-PPI: Towards Effective and Efficient Protein-Protein Interaction Prediction via Microenvironment-Aware Protein Embedding}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/18046},
}

@inproceedings{neurips2024_reactzyme_74507,
  title = {{ReactZyme: A Benchmark for Enzyme-Reaction Prediction}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/97442},
}

@inproceedings{aaai2024_cross_5527,
  title = {{Cross-Gate MLP with Protein Complex Invariant Embedding Is a One-Shot Antibody Designer}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29445},
}

@inproceedings{icml2021_a_38987,
  title = {{A Structured Observation Distribution for Generative Biological Sequence Prediction and Forecasting}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2021},
  url = {https://icml.cc/virtual/2021/poster/9725},
}

@inproceedings{neurips2023_avida_67246,
  title = {{AVIDa-hIL6: A Large-Scale VHH Dataset Produced from an Immunized Alpaca for Predicting Antigen-Antibody Interactions}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2023},
  url = {https://nips.cc/virtual/2023/poster/73664},
}

@inproceedings{icml2024_learning_45011,
  title = {{Learning to Predict Mutational Effects of Protein-Protein Interactions by Microenvironment-aware Hierarchical Prompt Learning}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/33441},
}

@inproceedings{neurips2020_learning_60184,
  title = {{Learning Mutational Semantics}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/17418},
}

@inproceedings{neurips2025_from_76507,
  title = {{From Likelihood to Fitness: Improving Variant Effect Prediction in Protein and Genome Language Models}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=K6M7QmN1wQ},
}

@inproceedings{neurips2024_ultrafast_71397,
  title = {{Ultrafast classical phylogenetic method beats large protein language models on variant effect prediction}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/95854},
}

@inproceedings{iclr2025_hotspot_83194,
  title = {{Hotspot-Driven Peptide Design via Multi-Fragment Autoregressive Extension}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/28614},
}

@inproceedings{aaai2025_synergy_10887,
  title = {{Synergy of GFlowNet and Protein Language Model Makes a Diverse Antibody Designer}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/34370},
}

@inproceedings{icml2024_geoab_43550,
  title = {{GeoAB: Towards Realistic Antibody Design and Reliable Affinity Maturation}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/34902},
}

@inproceedings{iclr2025_metalic_82250,
  title = {{Metalic: Meta-Learning In-Context with Protein Language Models}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/29540},
}

@inproceedings{iclr2026_a_84976,
  title = {{A New Paradigm for Genome-wide DNA Methylation Prediction Without Methylation Input}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2026},
  url = {https://openreview.net/forum?id=8wQ7Oc08vo},
}

@inproceedings{icml2025_affinityflow_46831,
  title = {{AffinityFlow: Guided Flows for Antibody Affinity Maturation}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/45745},
}

@inproceedings{neurips2024_generalized_72571,
  title = {{Generalized Protein Pocket Generation with Prior-Informed Flow Matching}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/94801},
}

@inproceedings{neurips2024_gflownet_73269,
  title = {{GFlowNet Assisted Biological Sequence Editing}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/94171},
}

@inproceedings{neurips2024_prospect_73444,
  title = {{PROSPECT PTMs: Rich Labeled Tandem Mass Spectrometry Dataset of Modified Peptides for Machine Learning in Proteomics}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/97558},
}

@inproceedings{neurips2025_augmenting_76519,
  title = {{Augmenting Biological Fitness Prediction Benchmarks with Landscapes Features from GraphFLA}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=KI8XRNjPI2},
}

@inproceedings{iclr2025_multi_80685,
  title = {{Multi-Modal and Multi-Attribute Generation of Single Cells with CFGen}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/31082},
}

@inproceedings{neurips2026_virogym_91331,
  title = {{ViroGym: Realistic Large-Scale Benchmarks for Evaluating Viral Proteins}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2026},
  url = {https://neurips.cc/virtual/2026/poster/139039},
}