Interpretability Beyond Classification Output: Semantic Bottleneck Networks

25 July 2019

M. Losch

Mario Fritz

Bernt Schiele

UQCV

ArXiv PDF HTML

Papers citing "Interpretability Beyond Classification Output: Semantic Bottleneck Networks"

23 / 23 papers shown

Title
Show and Tell: Visually Explainable Deep Neural Nets via Spatially-Aware Concept Bottleneck Models Itay Benou Tammy Riklin-Raviv 67 0 0 27 Feb 2025
COMIX: Compositional Explanations using Prototypes S. Sivaprasad D. Kangin Plamen Angelov Mario Fritz 145 0 0 10 Jan 2025
Image-guided topic modeling for interpretable privacy classification Alina Elena Baia Andrea Cavallaro 42 0 0 27 Sep 2024
Multi-Scale Grouped Prototypes for Interpretable Semantic Segmentation Hugo Porta Emanuele Dalsasso Diego Marcos D. Tuia 95 0 0 14 Sep 2024
DEPICT: Diffusion-Enabled Permutation Importance for Image Classification Tasks Sarah Jabbour Gregory Kondas Ella Kazerooni Michael Sjoding David Fouhey Jenna Wiens FAtt DiffM 47 1 0 19 Jul 2024
Automated Molecular Concept Generation and Labeling with Large Language Models Shichang Zhang Botao Xia Zimin Zhang Qianli Wu Fang Sun Ziniu Hu Yizhou Sun 43 0 0 13 Jun 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 37 6 0 04 Apr 2024
Interpreting Pretrained Language Models via Concept Bottlenecks Zhen Tan Lu Cheng Song Wang Yuan Bo Jundong Li Huan Liu LRM 32 20 0 08 Nov 2023
Editable User Profiles for Controllable Text Recommendation Sheshera Mysore Mahmood Jasim Andrew McCallum Hamed Zamani 15 15 0 09 Apr 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
Hierarchical Explanations for Video Action Recognition Sadaf Gulshad Teng Long N. V. Noord FAtt 18 6 0 01 Jan 2023
GlanceNets: Interpretabile, Leak-proof Concept-based Models Emanuele Marconato Andrea Passerini Stefano Teso 106 64 0 31 May 2022
Concept Embedding Analysis: A Review Gesina Schwalbe 32 28 0 25 Mar 2022
Editing a classifier by rewriting its prediction rules Shibani Santurkar Dimitris Tsipras Mahalaxmi Elango David Bau Antonio Torralba A. Madry KELM 177 89 0 02 Dec 2021
Image Classification with Consistent Supporting Evidence Peiqi Wang Ruizhi Liao Daniel Moyer Seth Berkowitz Steven Horng Polina Golland 34 2 0 13 Nov 2021
Toward a Unified Framework for Debugging Concept-based Models A. Bontempelli Fausto Giunchiglia Andrea Passerini Stefano Teso 20 4 0 23 Sep 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
A Comprehensive Taxonomy for Explainable Artificial Intelligence: A Systematic Survey of Surveys on Methods and Concepts Gesina Schwalbe Bettina Finzel XAI 26 184 0 15 May 2021
Towards a Collective Agenda on AI for Earth Science Data Analysis D. Tuia R. Roscher Jan Dirk Wegner Nathan Jacobs Xiaoxiang Zhu Gustau Camps-Valls AI4CE 39 68 0 11 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
Debiasing Concept-based Explanations with Causal Analysis M. T. Bahadori David Heckerman FAtt CML 11 38 0 22 Jul 2020
Adversarial examples in the physical world Alexey Kurakin Ian Goodfellow Samy Bengio SILM AAML 287 5,835 0 08 Jul 2016