Concept Bottleneck Models

9 July 2020

Pang Wei Koh

Thao Nguyen

Papers citing "Concept Bottleneck Models"

50 / 157 papers shown

Title
Towards Procedural Fairness: Uncovering Biases in How a Toxic Language Classifier Uses Sentiment Information I. Nejadgholi Esma Balkir Kathleen C. Fraser S. Kiritchenko 40 3 0 19 Oct 2022
TCNL: Transparent and Controllable Network Learning Via Embedding Human-Guided Concepts Zhihao Wang Chuang Zhu 24 1 0 07 Oct 2022
Causal Proxy Models for Concept-Based Model Explanations Zhengxuan Wu Karel DÓosterlinck Atticus Geiger Amir Zur Christopher Potts MILM 77 35 0 28 Sep 2022
Global Concept-Based Interpretability for Graph Neural Networks via Neuron Analysis Xuanyuan Han Pietro Barbiero Dobrik Georgiev Lucie Charlotte Magister Pietro Lió MILM 37 41 0 22 Aug 2022
Visual Interpretable and Explainable Deep Learning Models for Brain Tumor MRI and COVID-19 Chest X-ray Images Yusuf Brima M. Atemkeng FAtt MedIm 29 0 0 01 Aug 2022
Leveraging Explanations in Interactive Machine Learning: An Overview Stefano Teso Öznur Alkan Wolfgang Stammer Elizabeth M. Daly XAI FAtt LRM 26 62 0 29 Jul 2022
When are Post-hoc Conceptual Explanations Identifiable? Tobias Leemann Michael Kirchhof Yao Rong Enkelejda Kasneci Gjergji Kasneci 50 10 0 28 Jun 2022
Auditing Visualizations: Transparency Methods Struggle to Detect Anomalous Behavior Jean-Stanislas Denain Jacob Steinhardt AAML 42 7 0 27 Jun 2022
C-SENN: Contrastive Self-Explaining Neural Network Yoshihide Sawada Keigo Nakamura SSL 16 8 0 20 Jun 2022
GlanceNets: Interpretabile, Leak-proof Concept-based Models Emanuele Marconato Andrea Passerini Stefano Teso 106 64 0 31 May 2022
Post-hoc Concept Bottleneck Models Mert Yuksekgonul Maggie Wang James Zou 145 185 0 31 May 2022
Neural Basis Models for Interpretability Filip Radenovic Abhimanyu Dubey D. Mahajan FAtt 32 46 0 27 May 2022
Learnable Visual Words for Interpretable Image Recognition Wenxi Xiao Zhengming Ding Hongfu Liu VLM 25 2 0 22 May 2022
Leveraging Relational Information for Learning Weakly Disentangled Representations Andrea Valenti D. Bacciu CoGe DRL 29 5 0 20 May 2022
Clinical outcome prediction under hypothetical interventions -- a representation learning framework for counterfactual reasoning Yikuan Li M. Mamouei Shishir Rao A. Hassaine D. Canoy Thomas Lukasiewicz K. Rahimi G. Salimi-Khorshidi OOD CML AI4CE 31 1 0 15 May 2022
Perspectives on Incorporating Expert Feedback into Model Updates Valerie Chen Umang Bhatt Hoda Heidari Adrian Weller Ameet Talwalkar 30 11 0 13 May 2022
Adapting and Evaluating Influence-Estimation Methods for Gradient-Boosted Decision Trees Jonathan Brophy Zayd Hammoudeh Daniel Lowd TDI 27 22 0 30 Apr 2022
RelViT: Concept-guided Vision Transformer for Visual Relational Reasoning Xiaojian Ma Weili Nie Zhiding Yu Huaizu Jiang Chaowei Xiao Yuke Zhu Song-Chun Zhu Anima Anandkumar ViT LRM 30 19 0 24 Apr 2022
ConceptExplainer: Interactive Explanation for Deep Neural Networks from a Concept Perspective Jinbin Huang Aditi Mishra Bum Chul Kwon Chris Bryan FAtt HAI 43 31 0 04 Apr 2022
Do Vision-Language Pretrained Models Learn Composable Primitive Concepts? Tian Yun Usha Bhalla Ellie Pavlick Chen Sun ReLM CoGe VLM LRM 31 23 0 31 Mar 2022
Concept Embedding Analysis: A Review Gesina Schwalbe 32 28 0 25 Mar 2022
SemSup: Semantic Supervision for Simple and Scalable Zero-shot Generalization Austin W. Hanjie A. Deshpande Karthik Narasimhan VLM 36 2 0 26 Feb 2022
Human-Centered Concept Explanations for Neural Networks Chih-Kuan Yeh Been Kim Pradeep Ravikumar FAtt 37 25 0 25 Feb 2022
Towards Disentangling Information Paths with Coded ResNeXt Apostolos Avranas Marios Kountouris FAtt 17 1 0 10 Feb 2022
Debiased-CAM to mitigate systematic error with faithful visual explanations of machine learning Wencan Zhang Mariella Dimiccoli Brian Y. Lim FAtt 19 1 0 30 Jan 2022
Deeply Explain CNN via Hierarchical Decomposition Mingg-Ming Cheng Peng-Tao Jiang Linghao Han Liang Wang Philip H. S. Torr FAtt 53 15 0 23 Jan 2022
HIVE: Evaluating the Human Interpretability of Visual Explanations Sunnie S. Y. Kim Nicole Meister V. V. Ramaswamy Ruth C. Fong Olga Russakovsky 66 114 0 06 Dec 2021
Editing a classifier by rewriting its prediction rules Shibani Santurkar Dimitris Tsipras Mahalaxmi Elango David Bau Antonio Torralba A. Madry KELM 180 89 0 02 Dec 2021
Image Classification with Consistent Supporting Evidence Peiqi Wang Ruizhi Liao Daniel Moyer Seth Berkowitz Steven Horng Polina Golland 42 2 0 13 Nov 2021
Self-Interpretable Model with TransformationEquivariant Interpretation Yipei Wang Xiaoqian Wang 38 23 0 09 Nov 2021
Transparency of Deep Neural Networks for Medical Image Analysis: A Review of Interpretability Methods Zohaib Salahuddin Henry C. Woodruff A. Chatterjee Philippe Lambin 18 302 0 01 Nov 2021
Self-explaining Neural Network with Concept-based Explanations for ICU Mortality Prediction Sayantan Kumar Sean C. Yu Thomas Kannampallil Zachary B. Abrams Andrew Michelson Philip R. O. Payne FAtt 11 7 0 09 Oct 2021
Toward a Unified Framework for Debugging Concept-based Models A. Bontempelli Fausto Giunchiglia Andrea Passerini Stefano Teso 20 4 0 23 Sep 2021
A Framework for Learning Ante-hoc Explainable Models via Concepts Anirban Sarkar Deepak Vijaykeerthy Anindya Sarkar V. Balasubramanian LRM BDL 22 46 0 25 Aug 2021
Logic Explained Networks Gabriele Ciravegna Pietro Barbiero Francesco Giannini Marco Gori Pietro Lió Marco Maggini S. Melacci 37 69 0 11 Aug 2021
GCExplainer: Human-in-the-Loop Concept-based Explanations for Graph Neural Networks Lucie Charlotte Magister Dmitry Kazhdan Vikash Singh Pietro Lió 32 48 0 25 Jul 2021
Promises and Pitfalls of Black-Box Concept Learning Models Anita Mahinpei Justin Clark Isaac Lage Finale Doshi-Velez Weiwei Pan 31 91 0 24 Jun 2021
Entropy-based Logic Explanations of Neural Networks Pietro Barbiero Gabriele Ciravegna Francesco Giannini Pietro Lió Marco Gori S. Melacci FAtt XAI 25 78 0 12 Jun 2021
Rationalization through Concepts Diego Antognini Boi Faltings FAtt 27 19 0 11 May 2021
Do Concept Bottleneck Models Learn as Intended? Andrei Margeloiu Matthew Ashman Umang Bhatt Yanzhi Chen M. Jamnik Adrian Weller SLR 17 91 0 10 May 2021
Exploiting Explanations for Model Inversion Attacks Xu Zhao Wencan Zhang Xiao Xiao Brian Y. Lim MIACV 21 82 0 26 Apr 2021
Failing Conceptually: Concept-Based Explanations of Dataset Shift Maleakhi A. Wijaya Dmitry Kazhdan B. Dimanov M. Jamnik 9 7 0 18 Apr 2021
Deep Interpretable Models of Theory of Mind Ini Oguntola Dana Hughes Katia P. Sycara HAI 33 23 0 07 Apr 2021
Interpretable Machine Learning: Fundamental Principles and 10 Grand Challenges Cynthia Rudin Chaofan Chen Zhi Chen Haiyang Huang Lesia Semenova Chudi Zhong FaML AI4CE LRM 59 653 0 20 Mar 2021
An overview of artificial intelligence techniques for diagnosis of Schizophrenia based on magnetic resonance imaging modalities: Methods, challenges, and future works Delaram Sadeghi A. Shoeibi Navid Ghassemi Parisa Moridian Ali Khadem ... Juan M Gorriz F. Khozeimeh Yu-Dong Zhang S. Nahavandi U. Acharya 19 105 0 24 Feb 2021
NuCLS: A scalable crowdsourcing, deep learning approach and dataset for nucleus classification, localization and segmentation M. Amgad Lamees A. Atteya Hagar Hussein K. Mohammed Ehab Hafiz ... Critical Care David Manthey Atlanta D. Neurology Lurie Cancer Center 34 73 0 18 Feb 2021
Progressive Interpretation Synthesis: Interpreting Task Solving by Quantifying Previously Used and Unused Information Zhengqi He Taro Toyoizumi 19 1 0 08 Jan 2021
Debiased-CAM to mitigate image perturbations with faithful visual explanations of machine learning Wencan Zhang Mariella Dimiccoli Brian Y. Lim FAtt 24 18 0 10 Dec 2020
Interpretability and Explainability: A Machine Learning Zoo Mini-tour Ricards Marcinkevics Julia E. Vogt XAI 28 119 0 03 Dec 2020
Right for the Right Concept: Revising Neuro-Symbolic Concepts by Interacting with their Explanations Wolfgang Stammer P. Schramowski Kristian Kersting FAtt 14 107 0 25 Nov 2020