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

@inproceedings{neurips2020_bongard_59477,
  title = {{Bongard-LOGO: A New Benchmark for Human-Level Concept Learning and Reasoning}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/19062},
}

@inproceedings{neurips2024_vlg_71571,
  title = {{VLG-CBM: Training Concept Bottleneck Models with Vision-Language Guidance}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/95698},
}

@inproceedings{cvpr2025_hybrid_26540,
  title = {{Hybrid Concept Bottleneck Models}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2025},
  url = {https://cvpr.thecvf.com/virtual/2025/poster/33050},
}

@inproceedings{neurips2024_free_73122,
  title = {{Free Lunch in Pathology Foundation Model: Task-specific Model Adaptation with Concept-Guided Feature Enhancement}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/94308},
}

@inproceedings{aaai2025_v2c_11205,
  title = {{V2C-CBM: Building Concept Bottlenecks with Vision-to-Concept Tokenizer}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/32352},
}

@inproceedings{neurips2023_what_69689,
  title = {{What’s Left? Concept Grounding with Logic-Enhanced Foundation Models}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2023},
  url = {https://nips.cc/virtual/2023/poster/70248},
}

@inproceedings{neurips2024_coarse_72160,
  title = {{Coarse-to-Fine Concept Bottleneck Models}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/95178},
}

@inproceedings{aaai2026_partially_105556,
  title = {{Partially Shared Concept Bottleneck Models}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/38312},
}

@inproceedings{aaai2025_explanation_9054,
  title = {{Explanation Bottleneck Models}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/35495},
}

@inproceedings{iclr2024_faithful_35391,
  title = {{Faithful Vision-Language Interpretation via Concept Bottleneck Models}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/17682},
}

@inproceedings{icml2025_dcbm_46462,
  title = {{DCBM: Data-Efficient Visual Concept Bottleneck Models}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/46104},
}

@inproceedings{icml2026_prototype_49394,
  title = {{Prototype-Grounded Concept Models for Verifiable Concept Alignment}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=2A9FaOnzby},
}

@inproceedings{neurips2024_cosy_72129,
  title = {{CoSy: Evaluating Textual Explanations of Neurons}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/95204},
}

@inproceedings{neurips2024_explaining_74260,
  title = {{Explaining Datasets in Words: Statistical Models with Natural Language Parameters}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/93296},
}

@inproceedings{neurips2026_concepts_91040,
  title = {{Concepts Worth Having: Refining VLM-Guided Concept Bottleneck Models with Minimal Annotations}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2026},
  url = {https://neurips.cc/virtual/2026/poster/151925},
}

@inproceedings{cvpr2026_rethinking_97601,
  title = {{Rethinking Concept Bottleneck Models: From Pitfalls to Solutions}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2026},
  url = {https://openaccess.thecvf.com/content/CVPR2026/html/Tapli_Rethinking_Concept_Bottleneck_Models_From_Pitfalls_to_Solutions_CVPR_2026_paper.html},
}

@inproceedings{aaai2026_concepts_100684,
  title = {{Concepts from Representations: Post-hoc Concept Bottleneck Models via Sparse Decomposition of Visual Representations}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/42424},
}

@inproceedings{iclr2022_mapping_31548,
  title = {{Mapping Language Models to Grounded Conceptual Spaces}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2022},
  url = {https://iclr.cc/virtual/2022/poster/5992},
}

@inproceedings{icml2026_neuro_53327,
  title = {{Neuro-Fuzzy Concept Learning for Interpretable Large Multimodal Models}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=eVpMzC0bZs},
}

@inproceedings{iclr2026_escaping_85017,
  title = {{Escaping Low-Rank Traps: Interpretable Visual Concept Learning via Implicit Vector Quantization}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2026},
  url = {https://openreview.net/forum?id=9M2VrpAtR1},
}

@inproceedings{cvpr2026_rounded_98940,
  title = {{Rounded or Streamlined Head? Bridging Concept Bottleneck Models and Attribute-Described Object Parts}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2026},
  url = {https://openaccess.thecvf.com/content/CVPR2026/html/Liu_Rounded_or_Streamlined_Head_Bridging_Concept_Bottleneck_Models_and_Attribute-Described_CVPR_2026_paper.html},
}