% Key papers for Self-explaining and visual explanation networks (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{cvpr2017_network_12483,
  title = {{Network Dissection: Quantifying Interpretability of Deep Visual Representations}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2017},
}

@inproceedings{neurips2019_this_59085,
  title = {{This Looks Like That: Deep Learning for Interpretable Image Recognition}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/14571},
}

@inproceedings{iclr2017_visualizing_28213,
  title = {{Visualizing Deep Neural Network Decisions: Prediction Difference Analysis}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2017},
  url = {https://openreview.net/forum?id=BJ5UeU9xx},
}

@inproceedings{icml2018_interpretability_36759,
  title = {{Interpretability Beyond Feature Attribution: Quantitative Testing with Concept Activation Vectors (TCAV)}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2018},
  url = {https://icml.cc/virtual/2018/poster/2089},
}

@inproceedings{aaai2018_deep_102504,
  title = {{Deep Learning for Case-Based Reasoning Through Prototypes: A Neural Network That Explains Its Predictions}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2018},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/11771},
}

@inproceedings{neurips2018_towards_57718,
  title = {{Towards Robust Interpretability with Self-Explaining Neural Networks}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/11746},
}

@inproceedings{neurips2019_a_57793,
  title = {{A Benchmark for Interpretability Methods in Deep Neural Networks}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/14002},
}

@inproceedings{cvpr2021_neural_17494,
  title = {{Neural Prototype Trees for Interpretable Fine-Grained Image Recognition}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2021},
}

@inproceedings{cvpr2018_net2vec_13418,
  title = {{Net2Vec: Quantifying and Explaining How Concepts Are Encoded by Filters in Deep Neural Networks}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2018},
  url = {https://openaccess.thecvf.com/content_cvpr_2018/html/Fong_Net2Vec_Quantifying_and_CVPR_2018_paper.html},
}

@inproceedings{neurips2018_explanations_57113,
  title = {{Explanations based on the Missing: Towards Contrastive Explanations with Pertinent Negatives}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/11082},
}

@inproceedings{icml2020_interpretations_38338,
  title = {{Interpretations are Useful: Penalizing Explanations to Align Neural Networks with Prior Knowledge}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2020},
  url = {https://icml.cc/virtual/2020/poster/5914},
}

@inproceedings{aaai2023_improving_3885,
  title = {{Improving Interpretability of Deep Sequential Knowledge Tracing Models with Question-centric Cognitive Representations}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2023},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/26661},
}

@inproceedings{cvpr2020_a_15064,
  title = {{A Disentangling Invertible Interpretation Network for Explaining Latent Representations}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2020},
}

@inproceedings{aaai2020_cocox_101262,
  title = {{CoCoX: Generating Conceptual and Counterfactual Explanations via Fault-Lines}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2020},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/5643},
}

@inproceedings{neurips2018_deeppink_57019,
  title = {{DeepPINK: reproducible feature selection in deep neural networks}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/11829},
}

@inproceedings{cvpr2023_learning_21350,
  title = {{Learning Bottleneck Concepts in Image Classification}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2023},
  url = {https://cvpr.thecvf.com/virtual/2023/poster/22616},
}

@inproceedings{icml2018_discovering_36642,
  title = {{Discovering Interpretable Representations for Both Deep Generative and Discriminative Models}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2018},
  url = {https://icml.cc/virtual/2018/poster/1908},
}

@inproceedings{neurips2020_on_60458,
  title = {{On Completeness-aware Concept-Based Explanations in Deep Neural Networks}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/17843},
}

@inproceedings{cvpr2021_understanding_18071,
  title = {{Understanding Failures of Deep Networks via Robust Feature Extraction}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2021},
}

@inproceedings{cvpr2022_a_18199,
  title = {{A Framework for Learning Ante-Hoc Explainable Models via Concepts}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2022},
}

@inproceedings{aaai2024_deep_5648,
  title = {{Deep Unfolded Network with Intrinsic Supervision for Pan-Sharpening}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/28350},
}

@inproceedings{cvpr2024_mcpnet_24058,
  title = {{MCPNet: An Interpretable Classifier via Multi-Level Concept Prototypes}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/30830},
}

@inproceedings{aaai2024_keep_6375,
  title = {{Keep the Faith: Faithful Explanations in Convolutional Neural Networks for Case-Based Reasoning}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/28406},
}

@inproceedings{cvpr2025_finer_26266,
  title = {{Finer-CAM: Spotting the Difference Reveals Finer Details for Visual Explanation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2025},
  url = {https://cvpr.thecvf.com/virtual/2025/poster/32532},
}

@inproceedings{cvpr2024_www_25263,
  title = {{WWW: A Unified Framework for Explaining What Where and Why of Neural Networks by Interpretation of Neuron Concepts}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/31445},
}

@inproceedings{aaai2024_q_7030,
  title = {{Q-SENN: Quantized Self-Explaining Neural Networks}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/30145},
}

@inproceedings{aaai2024_towards_7608,
  title = {{Towards Modeling Uncertainties of Self-Explaining Neural Networks via Conformal Prediction}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29382},
}

@inproceedings{aaai2025_protoargnet_10391,
  title = {{ProtoArgNet: Interpretable Image Classification with Super-Prototypes and Argumentation}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/32173},
}

@inproceedings{cvpr2024_cape_22899,
  title = {{CAPE: CAM as a Probabilistic Ensemble for Enhanced DNN Interpretation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/31245},
}

@inproceedings{icml2024_don_45519,
  title = {{Don't trust your eyes: on the (un)reliability of feature visualizations}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/32933},
}

@inproceedings{cvpr2025_diffcam_25932,
  title = {{DiffCAM: Data-Driven Saliency Maps by Capturing Feature Differences}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2025},
  url = {https://cvpr.thecvf.com/virtual/2025/poster/32489},
}

@inproceedings{cvpr2025_towards_27903,
  title = {{Towards Fine-Grained Interpretability: Counterfactual Explanations for Misclassification with Saliency Partition}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2025},
  url = {https://cvpr.thecvf.com/virtual/2025/poster/34905},
}

@inproceedings{icml2024_improving_44225,
  title = {{Improving Prototypical Visual Explanations with Reward Reweighing, Reselection, and Retraining}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/34227},
}

@inproceedings{neurips2024_deep_70528,
  title = {{Deep Support Vectors}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/96584},
}

@inproceedings{aaai2024_understanding_7683,
  title = {{Understanding Distributed Representations of Concepts in Deep Neural Networks without Supervision}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/28999},
}

@inproceedings{aaai2025_interpretable_9593,
  title = {{Interpretable Failure Detection with Human-Level Concepts}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/34831},
}

@inproceedings{aaai2025_know2vec_9646,
  title = {{Know2Vec: A Black-Box Proxy for Neural Network Retrieval}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/34241},
}

@inproceedings{cvpr2025_show_27664,
  title = {{Show and Tell: Visually Explainable Deep Neural Nets via Spatially-Aware Concept Bottleneck Models}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2025},
  url = {https://cvpr.thecvf.com/virtual/2025/poster/33212},
}

@inproceedings{icml2024_post_45161,
  title = {{Post-hoc Part-Prototype Networks}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/33291},
}

@inproceedings{aaai2026_from_106972,
  title = {{From Attribution to Action: Jointly ALIGNing Predictions and Explanations}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/39324},
}