Concept Embedding Analysis: A Review

25 March 2022

Papers citing "Concept Embedding Analysis: A Review"

20 / 20 papers shown

Title
If Concept Bottlenecks are the Question, are Foundation Models the Answer? Nicola Debole Pietro Barbiero Francesco Giannini Andrea Passerini Stefano Teso Emanuele Marconato 104 0 0 28 Apr 2025
On Background Bias of Post-Hoc Concept Embeddings in Computer Vision DNNs Gesina Schwalbe Georgii Mikriukov Edgar Heinert Stavros Gerolymatos Mert Keser Alois Knoll Matthias Rottmann Annika Mütze 31 0 0 11 Apr 2025
Explaining Domain Shifts in Language: Concept erasing for Interpretable Image Classification Zequn Zeng Yudi Su Jianqiao Sun Tiansheng Wen Hao Zhang Zhengjue Wang Bo Chen Hongwei Liu Jiawei Ma VLM 58 0 0 24 Mar 2025
Shortcuts and Identifiability in Concept-based Models from a Neuro-Symbolic Lens Samuele Bortolotti Emanuele Marconato Paolo Morettin Andrea Passerini Stefano Teso 53 2 0 16 Feb 2025
Unveiling Ontological Commitment in Multi-Modal Foundation Models Mert Keser Gesina Schwalbe Niki Amini-Naieni Matthias Rottmann Alois Knoll 21 1 0 25 Sep 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
Incremental Residual Concept Bottleneck Models Chenming Shang Shiji Zhou Hengyuan Zhang Xinzhe Ni Yujiu Yang Yuwang Wang 34 14 0 13 Apr 2024
Understanding Multimodal Deep Neural Networks: A Concept Selection View Chenming Shang Hengyuan Zhang Hao Wen Yujiu Yang 38 5 0 13 Apr 2024
Enhancing Interpretability of Vertebrae Fracture Grading using Human-interpretable Prototypes Poulami Sinhamahapatra Suprosanna Shit Anjany Sekuboyina M. Husseini D. Schinz Nicolas Lenhart Bjoern H. Menze Jan Kirschke Karsten Roscher Stephan Guennemann 37 1 0 03 Apr 2024
Concept Distillation: Leveraging Human-Centered Explanations for Model Improvement Avani Gupta Saurabh Saini P. J. Narayanan 23 6 0 26 Nov 2023
From Neural Activations to Concepts: A Survey on Explaining Concepts in Neural Networks Jae Hee Lee Sergio Lanza Stefan Wermter 14 8 0 18 Oct 2023
Interpretability is in the Mind of the Beholder: A Causal Framework for Human-interpretable Representation Learning Emanuele Marconato Andrea Passerini Stefano Teso 14 13 0 14 Sep 2023
How Faithful are Self-Explainable GNNs? Marc Christiansen Lea Villadsen Zhiqiang Zhong Stefano Teso Davide Mottin 18 3 0 29 Aug 2023
A Unified Concept-Based System for Local, Global, and Misclassification Explanations Fatemeh Aghaeipoor D. Asgarian Mohammad Sabokrou FAtt 19 0 0 06 Jun 2023
Revealing Similar Semantics Inside CNNs: An Interpretable Concept-based Comparison of Feature Spaces Georgii Mikriukov Gesina Schwalbe Christian Hellert Korinna Bade 11 2 0 30 Apr 2023
Evaluating the Stability of Semantic Concept Representations in CNNs for Robust Explainability Georgii Mikriukov Gesina Schwalbe Christian Hellert Korinna Bade FAtt 16 8 0 28 Apr 2023
Changes from Classical Statistics to Modern Statistics and Data Science Kai Zhang Shan-Yu Liu M. Xiong 26 0 0 30 Oct 2022
LAP: An Attention-Based Module for Concept Based Self-Interpretation and Knowledge Injection in Convolutional Neural Networks Rassa Ghavami Modegh Ahmadali Salimi Alireza Dizaji Hamid R. Rabiee FAtt 22 0 0 27 Jan 2022
Weakly Supervised Multi-task Learning for Concept-based Explainability Catarina Belém Vladimir Balayan Pedro Saleiro P. Bizarro 73 10 0 26 Apr 2021
On Completeness-aware Concept-Based Explanations in Deep Neural Networks Chih-Kuan Yeh Been Kim Sercan Ö. Arik Chun-Liang Li Tomas Pfister Pradeep Ravikumar FAtt 120 297 0 17 Oct 2019