Concept Bottleneck Models

9 July 2020

Pang Wei Koh

Thao Nguyen

Papers citing "Concept Bottleneck Models"

50 / 154 papers shown

Title
Data Alignment for Zero-Shot Concept Generation in Dermatology AI S. Gadgil Mahtab Bigverdi MedIm AI4MH VLM 36 0 0 19 Apr 2024
Pre-trained Vision-Language Models Learn Discoverable Visual Concepts Yuan Zang Tian Yun Hao Tan Trung Bui Chen Sun VLM CoGe 58 9 0 19 Apr 2024
Generating Counterfactual Trajectories with Latent Diffusion Models for Concept Discovery Payal Varshney Adriano Lucieri Christoph Balada Andreas Dengel Sheraz Ahmed MedIm DiffM 53 4 0 16 Apr 2024
Understanding Multimodal Deep Neural Networks: A Concept Selection View Chenming Shang Hengyuan Zhang Hao Wen Yujiu Yang 43 5 0 13 Apr 2024
Sparse Concept Bottleneck Models: Gumbel Tricks in Contrastive Learning Andrei Semenov Vladimir Ivanov Aleksandr Beznosikov Alexander Gasnikov 42 6 0 04 Apr 2024
Improving deep learning with prior knowledge and cognitive models: A survey on enhancing explainability, adversarial robustness and zero-shot learning F. Mumuni A. Mumuni AAML 37 5 0 11 Mar 2024
Interpreting CLIP with Sparse Linear Concept Embeddings (SpLiCE) Usha Bhalla Alexander X. Oesterling Suraj Srinivas Flavio du Pin Calmon Himabindu Lakkaraju 41 35 0 16 Feb 2024
Beyond Concept Bottleneck Models: How to Make Black Boxes Intervenable? Sonia Laguna Ricards Marcinkevics Moritz Vandenhirtz Julia E. Vogt 35 17 0 24 Jan 2024
3VL: Using Trees to Improve Vision-Language Models' Interpretability Nir Yellinek Leonid Karlinsky Raja Giryes CoGe VLM 49 4 0 28 Dec 2023
CEIR: Concept-based Explainable Image Representation Learning Yan Cui Shuhong Liu Liuzhuozheng Li Zhiyuan Yuan SSL VLM 31 3 0 17 Dec 2023
Concept Distillation: Leveraging Human-Centered Explanations for Model Improvement Avani Gupta Saurabh Saini P. J. Narayanan 25 6 0 26 Nov 2023
Auxiliary Losses for Learning Generalizable Concept-based Models Ivaxi Sheth Samira Ebrahimi Kahou 32 24 0 18 Nov 2023
Interpreting Pretrained Language Models via Concept Bottlenecks Zhen Tan Lu Cheng Song Wang Yuan Bo Wenlin Yao Huan Liu LRM 32 20 0 08 Nov 2023
Codebook Features: Sparse and Discrete Interpretability for Neural Networks Alex Tamkin Mohammad Taufeeque Noah D. Goodman 32 27 0 26 Oct 2023
Coarse-to-Fine Concept Bottleneck Models Konstantinos P. Panousis Dino Ienco Diego Marcos 28 5 0 03 Oct 2023
Automatic Concept Embedding Model (ACEM): No train-time concepts, No issue! Rishabh Jain LRM 27 0 0 07 Sep 2023
Prototype-based Dataset Comparison Nanne van Noord 31 6 0 05 Sep 2023
The Promise and Peril of Artificial Intelligence -- Violet Teaming Offers a Balanced Path Forward A. Titus Adam Russell 36 1 0 28 Aug 2023
LR-XFL: Logical Reasoning-based Explainable Federated Learning Yanci Zhang Hanyou Yu LRM 24 7 0 24 Aug 2023
Discriminative Feature Attributions: Bridging Post Hoc Explainability and Inherent Interpretability Usha Bhalla Suraj Srinivas Himabindu Lakkaraju FAtt CML 29 6 0 27 Jul 2023
Uncovering Unique Concept Vectors through Latent Space Decomposition Mara Graziani Laura Mahony An-phi Nguyen Henning Muller Vincent Andrearczyk 43 4 0 13 Jul 2023
Exploring the Lottery Ticket Hypothesis with Explainability Methods: Insights into Sparse Network Performance Shantanu Ghosh Kayhan Batmanghelich 30 0 0 07 Jul 2023
Backpack Language Models John Hewitt John Thickstun Christopher D. Manning Percy Liang KELM 13 16 0 26 May 2023
Learning Interpretable Style Embeddings via Prompting LLMs Ajay Patel D. Rao Ansh Kothary Kathleen McKeown Chris Callison-Burch 37 23 0 22 May 2023
MProtoNet: A Case-Based Interpretable Model for Brain Tumor Classification with 3D Multi-parametric Magnetic Resonance Imaging Yuanyuan Wei Roger Tam Xiaoying Tang MedIm 16 12 0 13 Apr 2023
Coherent Concept-based Explanations in Medical Image and Its Application to Skin Lesion Diagnosis Cristiano Patrício João C. Neves Luís F. Teixeira MedIm FAtt 24 17 0 10 Apr 2023
Editable User Profiles for Controllable Text Recommendation Sheshera Mysore Mahmood Jasim Andrew McCallum Hamed Zamani 15 16 0 09 Apr 2023
UFO: A unified method for controlling Understandability and Faithfulness Objectives in concept-based explanations for CNNs V. V. Ramaswamy Sunnie S. Y. Kim Ruth C. Fong Olga Russakovsky 29 0 0 27 Mar 2023
Learning with Explanation Constraints Rattana Pukdee Dylan Sam J. Zico Kolter Maria-Florina Balcan Pradeep Ravikumar FAtt 32 6 0 25 Mar 2023
Towards Learning and Explaining Indirect Causal Effects in Neural Networks Abbaavaram Gowtham Reddy Saketh Bachu Harsh Nilesh Pathak Ben Godfrey V. Balasubramanian V. Varshaneya Satya Narayanan Kar CML 31 0 0 24 Mar 2023
Take 5: Interpretable Image Classification with a Handful of Features Thomas Norrenbrock Marco Rudolph Bodo Rosenhahn FAtt 40 7 0 23 Mar 2023
ICICLE: Interpretable Class Incremental Continual Learning Dawid Rymarczyk Joost van de Weijer Bartosz Zieliñski Bartlomiej Twardowski CLL 32 28 0 14 Mar 2023
Concept Learning for Interpretable Multi-Agent Reinforcement Learning Renos Zabounidis Joseph Campbell Simon Stepputtis Dana Hughes Katia P. Sycara 31 15 0 23 Feb 2023
Towards a Deeper Understanding of Concept Bottleneck Models Through End-to-End Explanation Jack Furby Daniel Cunnington Dave Braines Alun D. Preece 14 6 0 07 Feb 2023
Variational Information Pursuit for Interpretable Predictions Aditya Chattopadhyay Kwan Ho Ryan Chan B. Haeffele D. Geman René Vidal DRL 21 10 0 06 Feb 2023
ProtoSeg: Interpretable Semantic Segmentation with Prototypical Parts Mikolaj Sacha Dawid Rymarczyk Lukasz Struski Jacek Tabor Bartosz Zieliñski VLM 32 29 0 28 Jan 2023
Learning Modulo Theories Matt Fredrikson Kaiji Lu Saranya Vijayakumar S. Jha Vijay Ganesh Zifan Wang NAI OffRL 43 0 0 26 Jan 2023
Img2Tab: Automatic Class Relevant Concept Discovery from StyleGAN Features for Explainable Image Classification Y. Song S. K. Shyn Kwang-su Kim VLM 21 5 0 16 Jan 2023
Hierarchical Explanations for Video Action Recognition Sadaf Gulshad Teng Long Nanne van Noord FAtt 23 6 0 01 Jan 2023
Impossibility Theorems for Feature Attribution Blair Bilodeau Natasha Jaques Pang Wei Koh Been Kim FAtt 20 68 0 22 Dec 2022
Adapting to Latent Subgroup Shifts via Concepts and Proxies Ibrahim M. Alabdulmohsin Nicole Chiou Alexander DÁmour A. Gretton Sanmi Koyejo Matt J. Kusner Stephen R. Pfohl Olawale Salaudeen Jessica Schrouff Katherine Tsai 68 9 0 21 Dec 2022
On the Relationship Between Explanation and Prediction: A Causal View Amir-Hossein Karimi Krikamol Muandet Simon Kornblith Bernhard Schölkopf Been Kim FAtt CML 29 14 0 13 Dec 2022
Intermediate Entity-based Sparse Interpretable Representation Learning Diego Garcia-Olano Yasumasa Onoe Joydeep Ghosh Byron C. Wallace 19 2 0 03 Dec 2022
Understanding and Enhancing Robustness of Concept-based Models Sanchit Sinha Mengdi Huai Jianhui Sun Aidong Zhang AAML 28 18 0 29 Nov 2022
Towards Human-Interpretable Prototypes for Visual Assessment of Image Classification Models Poulami Sinhamahapatra Lena Heidemann Maureen Monnet Karsten Roscher 39 5 0 22 Nov 2022
Learn to explain yourself, when you can: Equipping Concept Bottleneck Models with the ability to abstain on their concept predictions J. Lockhart Daniele Magazzeni Manuela Veloso 17 4 0 21 Nov 2022
Language in a Bottle: Language Model Guided Concept Bottlenecks for Interpretable Image Classification Yue Yang Artemis Panagopoulou Shenghao Zhou Daniel Jin Chris Callison-Burch Mark Yatskar 40 211 0 21 Nov 2022
Boosting Object Representation Learning via Motion and Object Continuity Quentin Delfosse Wolfgang Stammer Thomas Rothenbacher Dwarak Vittal Kristian Kersting OCL 37 20 0 16 Nov 2022
Interpretable Few-shot Learning with Online Attribute Selection M. Zarei Majid Komeili FAtt 35 1 0 16 Nov 2022
Emergence of Concepts in DNNs? Tim Räz 21 0 0 11 Nov 2022