A Holistic Approach to Unifying Automatic Concept Extraction and Concept Importance Estimation

11 June 2023

Papers citing "A Holistic Approach to Unifying Automatic Concept Extraction and Concept Importance Estimation"

47 / 47 papers shown

Title
The Dual Power of Interpretable Token Embeddings: Jailbreaking Attacks and Defenses for Diffusion Model Unlearning Siyi Chen Yimeng Zhang Sijia Liu Q. Qu AAML 55 0 0 30 Apr 2025
Interpreting the Linear Structure of Vision-language Model Embedding Spaces Isabel Papadimitriou Huangyuan Su Thomas Fel Naomi Saphra Sham Kakade Stephanie Gil VLM 40 0 0 16 Apr 2025
Towards Spatially-Aware and Optimally Faithful Concept-Based Explanations Shubham Kumar Dwip Dalal Narendra Ahuja 14 0 0 15 Apr 2025
Towards Human-Understandable Multi-Dimensional Concept Discovery Arne Grobrugge Niklas Kühl G. Satzger Philipp Spitzer 44 0 0 24 Mar 2025
Representational Similarity via Interpretable Visual Concepts Neehar Kondapaneni Oisin Mac Aodha Pietro Perona DRL 65 0 0 19 Mar 2025
CoE: Chain-of-Explanation via Automatic Visual Concept Circuit Description and Polysemanticity Quantification Wenlong Yu Qilong Wang Chuang Liu Dong Li Q. Hu LRM 58 0 0 19 Mar 2025
Intra-neuronal attention within language models Relationships between activation and semantics Michael Pichat William Pogrund Paloma Pichat Armanouche Gasparian Samuel Demarchi Corbet Alois Georgeon Michael Veillet-Guillem MILM 35 0 0 17 Mar 2025
Escaping Plato's Cave: Robust Conceptual Reasoning through Interpretable 3D Neural Object Volumes Nhi Pham Bernt Schiele Adam Kortylewski Jonas Fischer 46 0 0 17 Mar 2025
Conceptualizing Uncertainty Isaac Roberts Alexander Schulz Sarah Schroeder Fabian Hinder Barbara Hammer UD 67 0 0 05 Mar 2025
Synthetic Categorical Restructuring large Or How AIs Gradually Extract Efficient Regularities from Their Experience of the World Michael Pichat William Pogrund Paloma Pichat Armanouche Gasparian Samuel Demarchi Martin Corbet Alois Georgeon Theo Dasilva Michael Veillet-Guillem 41 1 0 25 Feb 2025
Universal Sparse Autoencoders: Interpretable Cross-Model Concept Alignment Harrish Thasarathan Julian Forsyth Thomas Fel M. Kowal Konstantinos G. Derpanis 91 7 0 06 Feb 2025
COMIX: Compositional Explanations using Prototypes S. Sivaprasad D. Kangin Plamen Angelov Mario Fritz 49 0 0 10 Jan 2025
ConSim: Measuring Concept-Based Explanations' Effectiveness with Automated Simulatability Antonin Poché Alon Jacovi Agustin Picard Victor Boutin Fanny Jourdan 31 2 0 10 Jan 2025
Analyzing Fine-tuning Representation Shift for Multimodal LLMs Steering alignment Pegah Khayatan Mustafa Shukor Jayneel Parekh Matthieu Cord LLMSV 38 1 0 06 Jan 2025
Explainable and Interpretable Multimodal Large Language Models: A Comprehensive Survey Yunkai Dang Kaichen Huang Jiahao Huo Yibo Yan S. Huang ... Kun Wang Yong Liu Jing Shao Hui Xiong Xuming Hu LRM 96 14 0 03 Dec 2024
Explaining the Impact of Training on Vision Models via Activation Clustering Ahcène Boubekki Samuel G. Fadel Sebastian Mair 89 0 0 29 Nov 2024
GIFT: A Framework for Global Interpretable Faithful Textual Explanations of Vision Classifiers Éloi Zablocki Valentin Gerard Amaia Cardiel Eric Gaussier Matthieu Cord Eduardo Valle 66 0 0 23 Nov 2024
Towards Utilising a Range of Neural Activations for Comprehending Representational Associations Laura O'Mahony Nikola S. Nikolov David JP O'Sullivan 28 0 0 15 Nov 2024
Local vs distributed representations: What is the right basis for interpretability? Julien Colin L. Goetschalckx Thomas Fel Victor Boutin Jay Gopal Thomas Serre Nuria Oliver HAI 16 2 0 06 Nov 2024
ConLUX: Concept-Based Local Unified Explanations Junhao Liu Haonan Yu Xin Zhang FAtt LRM 21 0 0 16 Oct 2024
One Wave to Explain Them All: A Unifying Perspective on Post-hoc Explainability Gabriel Kasmi Amandine Brunetto Thomas Fel Jayneel Parekh AAML FAtt 19 0 0 02 Oct 2024
Concept-Based Explanations in Computer Vision: Where Are We and Where Could We Go? Jae Hee Lee Georgii Mikriukov Gesina Schwalbe Stefan Wermter D. Wolter 48 2 0 20 Sep 2024
Trustworthy Conceptual Explanations for Neural Networks in Robot Decision-Making Som Sagar Aditya Taparia Harsh Mankodiya Pranav M Bidare Yifan Zhou Ransalu Senanayake FAtt 23 0 0 16 Sep 2024
Decompose the model: Mechanistic interpretability in image models with Generalized Integrated Gradients (GIG) Yearim Kim Sangyu Han Sangbum Han Nojun Kwak 40 0 0 03 Sep 2024
Explainable Concept Generation through Vision-Language Preference Learning Aditya Taparia Som Sagar Ransalu Senanayake FAtt 21 2 0 24 Aug 2024
Pruning By Explaining Revisited: Optimizing Attribution Methods to Prune CNNs and Transformers Sayed Mohammad Vakilzadeh Hatefi Maximilian Dreyer Reduan Achtibat Thomas Wiegand Wojciech Samek Sebastian Lapuschkin ViT 14 1 0 22 Aug 2024
Understanding Visual Feature Reliance through the Lens of Complexity Thomas Fel Louis Bethune Andrew Kyle Lampinen Thomas Serre Katherine Hermann FAtt CoGe 17 6 0 08 Jul 2024
Concept Bottleneck Models Without Predefined Concepts Simon Schrodi Julian Schur Max Argus Thomas Brox 20 9 0 04 Jul 2024
Probabilistic Conceptual Explainers: Trustworthy Conceptual Explanations for Vision Foundation Models Hengyi Wang Shiwei Tan Hao Wang BDL 27 6 0 18 Jun 2024
Concept-skill Transferability-based Data Selection for Large Vision-Language Models Jaewoo Lee Boyang Li Sung Ju Hwang VLM 33 8 0 16 Jun 2024
A Concept-Based Explainability Framework for Large Multimodal Models Jayneel Parekh Pegah Khayatan Mustafa Shukor A. Newson Matthieu Cord 19 16 0 12 Jun 2024
Understanding Inhibition Through Maximally Tense Images Chris Hamblin Srijani Saha Talia Konkle George Alvarez FAtt 19 0 0 08 Jun 2024
DISCRET: Synthesizing Faithful Explanations For Treatment Effect Estimation Yinjun Wu Mayank Keoliya Kan Chen Neelay Velingker Ziyang Li E. Getzen Qi Long Mayur Naik Ravi B. Parikh Eric Wong 27 1 0 02 Jun 2024
Reactive Model Correction: Mitigating Harm to Task-Relevant Features via Conditional Bias Suppression Dilyara Bareeva Maximilian Dreyer Frederik Pahde Wojciech Samek Sebastian Lapuschkin KELM 58 1 0 15 Apr 2024
WWW: A Unified Framework for Explaining What, Where and Why of Neural Networks by Interpretation of Neuron Concepts Yong Hyun Ahn Hyeon Bae Kim Seong Tae Kim 14 4 0 29 Feb 2024
Interpreting CLIP with Sparse Linear Concept Embeddings (SpLiCE) Usha Bhalla Alexander X. Oesterling Suraj Srinivas Flavio du Pin Calmon Himabindu Lakkaraju 21 35 0 16 Feb 2024
Understanding Video Transformers via Universal Concept Discovery M. Kowal Achal Dave Rares Ambrus Adrien Gaidon Konstantinos G. Derpanis P. Tokmakov ViT 27 2 0 19 Jan 2024
Understanding the (Extra-)Ordinary: Validating Deep Model Decisions with Prototypical Concept-based Explanations Maximilian Dreyer Reduan Achtibat Wojciech Samek Sebastian Lapuschkin 27 10 0 28 Nov 2023
On the Foundations of Shortcut Learning Katherine Hermann Hossein Mobahi Thomas Fel M. C. Mozer VLM 17 25 0 24 Oct 2023
Interpretability is in the Mind of the Beholder: A Causal Framework for Human-interpretable Representation Learning Emanuele Marconato Andrea Passerini Stefano Teso 4 13 0 14 Sep 2023
The Hidden Language of Diffusion Models Hila Chefer Oran Lang Mor Geva Volodymyr Polosukhin Assaf Shocher Michal Irani Inbar Mosseri Lior Wolf DiffM 20 26 0 01 Jun 2023
Quantifying and Learning Static vs. Dynamic Information in Deep Spatiotemporal Networks M. Kowal Mennatullah Siam Md. Amirul Islam Neil D. B. Bruce Richard P. Wildes Konstantinos G. Derpanis FAtt 6 3 0 03 Nov 2022
Toy Models of Superposition Nelson Elhage Tristan Hume Catherine Olsson Nicholas Schiefer T. Henighan ... Sam McCandlish Jared Kaplan Dario Amodei Martin Wattenberg C. Olah AAML MILM 117 314 0 21 Sep 2022
HIVE: Evaluating the Human Interpretability of Visual Explanations Sunnie S. Y. Kim Nicole Meister V. V. Ramaswamy Ruth C. Fong Olga Russakovsky 58 112 0 06 Dec 2021
Look at the Variance! Efficient Black-box Explanations with Sobol-based Sensitivity Analysis Thomas Fel Rémi Cadène Mathieu Chalvidal Matthieu Cord David Vigouroux Thomas Serre MLAU FAtt AAML 109 57 0 07 Nov 2021
Formalizing Trust in Artificial Intelligence: Prerequisites, Causes and Goals of Human Trust in AI Alon Jacovi Ana Marasović Tim Miller Yoav Goldberg 241 417 0 15 Oct 2020
Towards A Rigorous Science of Interpretable Machine Learning Finale Doshi-Velez Been Kim XAI FaML 225 3,658 0 28 Feb 2017