Network Dissection: Quantifying Interpretability of Deep Visual Representations

19 April 2017

Antonio Torralba

Papers citing "Network Dissection: Quantifying Interpretability of Deep Visual Representations"

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Title
Perceptual Group Tokenizer: Building Perception with Iterative Grouping Zhiwei Deng Ting Chen Yang Li ViT VLM 75 2 0 30 Nov 2023
Understanding the (Extra-)Ordinary: Validating Deep Model Decisions with Prototypical Concept-based Explanations Maximilian Dreyer Reduan Achtibat Wojciech Samek Sebastian Lapuschkin 60 12 0 28 Nov 2023
A Cross Attention Approach to Diagnostic Explainability using Clinical Practice Guidelines for Depression Sumit Dalal Deepa Tilwani Kaushik Roy Manas Gaur Sarika Jain V. Shalin Amit P. Sheth 84 7 0 23 Nov 2023
Labeling Neural Representations with Inverse Recognition Kirill Bykov Laura Kopf Shinichi Nakajima Marius Kloft Marina M.-C. Höhne BDL 122 20 0 22 Nov 2023
Representing visual classification as a linear combination of words Shobhit Agarwal Yevgeniy R. Semenov William Lotter 95 1 0 18 Nov 2023
Finding and Editing Multi-Modal Neurons in Pre-Trained Transformers Haowen Pan Yixin Cao Xiaozhi Wang Xun Yang Meng Wang KELM 108 27 0 13 Nov 2023
Towards A Unified Neural Architecture for Visual Recognition and Reasoning Calvin Luo Boqing Gong Ting Chen Chen Sun OCL ObjD 52 1 0 10 Nov 2023
A Simple Interpretable Transformer for Fine-Grained Image Classification and Analysis Dipanjyoti Paul A. Chowdhury Xinqi Xiong Feng-Ju Chang David Carlyn ... Daniel Rubenstein Charles V. Stewart Tanya Berger-Wolf Yu-Chuan Su Wei-Lun Chao ViT 103 18 0 07 Nov 2023
InterVLS: Interactive Model Understanding and Improvement with Vision-Language Surrogates Jinbin Huang Wenbin He Liangke Gou Liu Ren Chris Bryan VLM 54 1 0 06 Nov 2023
SoK: Memorisation in machine learning Dmitrii Usynin Moritz Knolle Georgios Kaissis 99 1 0 06 Nov 2023
Explaining the Decisions of Deep Policy Networks for Robotic Manipulations Seongun Kim Jaesik Choi 48 4 0 30 Oct 2023
Towards a fuller understanding of neurons with Clustered Compositional Explanations Biagio La Rosa Leilani H. Gilpin Roberto Capobianco 58 9 0 27 Oct 2023
Understanding Parameter Saliency via Extreme Value Theory Shuo Wang Issei Sato AAML FAtt 34 0 0 27 Oct 2023
This Reads Like That: Deep Learning for Interpretable Natural Language Processing Claudio Fanconi Moritz Vandenhirtz Severin Husmann Julia E. Vogt FAtt 70 2 0 25 Oct 2023
Driving through the Concept Gridlock: Unraveling Explainability Bottlenecks in Automated Driving J. Echterhoff An Yan Kyungtae Han Amr Abdelraouf Rohit Gupta Julian McAuley 60 7 0 25 Oct 2023
Corrupting Neuron Explanations of Deep Visual Features Divyansh Srivastava Tuomas P. Oikarinen Tsui-Wei Weng FAtt AAML 44 2 0 25 Oct 2023
Instance-wise Linearization of Neural Network for Model Interpretation Zhimin Li Shusen Liu B. Kailkhura Timo Bremer Valerio Pascucci MILM FAtt 62 0 0 25 Oct 2023
Zone Evaluation: Revealing Spatial Bias in Object Detection Zhaohui Zheng Yuming Chen Qibin Hou Xiang Li Ping Wang Ming-Ming Cheng ObjD 116 4 0 20 Oct 2023
Understanding Addition in Transformers Philip Quirke Fazl Barez 153 19 0 19 Oct 2023
Frozen Transformers in Language Models Are Effective Visual Encoder Layers Ziqi Pang Ziyang Xie Yunze Man Yu-Xiong Wang 146 27 0 19 Oct 2023
Getting aligned on representational alignment Ilia Sucholutsky Lukas Muttenthaler Adrian Weller Andi Peng Andreea Bobu ... Thomas Unterthiner Andrew Kyle Lampinen Klaus-Robert Muller M. Toneva Thomas Griffiths 158 93 0 18 Oct 2023
Removing Spurious Concepts from Neural Network Representations via Joint Subspace Estimation Floris Holstege Bram Wouters Noud van Giersbergen C. Diks 101 2 0 18 Oct 2023
From Neural Activations to Concepts: A Survey on Explaining Concepts in Neural Networks Jae Hee Lee Sergio Lanza Stefan Wermter 73 10 0 18 Oct 2023
Interpreting and Controlling Vision Foundation Models via Text Explanations Haozhe Chen Junfeng Yang Carl Vondrick Chengzhi Mao 83 3 0 16 Oct 2023
Automated Natural Language Explanation of Deep Visual Neurons with Large Models Chenxu Zhao Wei Qian Yucheng Shi Mengdi Huai Ninghao Liu 44 3 0 16 Oct 2023
What Do Deep Saliency Models Learn about Visual Attention? Shi Chen Ming Jiang Qi Zhao FAtt 35 2 0 14 Oct 2023
Learning Transferable Conceptual Prototypes for Interpretable Unsupervised Domain Adaptation Junyu Gao Xinhong Ma Changsheng Xu 107 5 0 12 Oct 2023
NeuroInspect: Interpretable Neuron-based Debugging Framework through Class-conditional Visualizations Yeong-Joon Ju Ji-Hoon Park Seong-Whan Lee AAML 46 0 0 11 Oct 2023
Latent Diffusion Counterfactual Explanations Karim Farid Simon Schrodi Max Argus Thomas Brox DiffM 99 14 0 10 Oct 2023
The Importance of Prompt Tuning for Automated Neuron Explanations Justin Lee Tuomas P. Oikarinen Arjun Chatha Keng-Chi Chang Yilan Chen Tsui-Wei Weng LRM 68 8 0 09 Oct 2023
DiPS: Discriminative Pseudo-Label Sampling with Self-Supervised Transformers for Weakly Supervised Object Localization Shakeeb Murtaza Soufiane Belharbi M. Pedersoli Aydin Sarraf Eric Granger WSOL 121 9 0 09 Oct 2023
Deep Concept Removal Yegor Klochkov Jean-François Ton Ruocheng Guo Yang Liu Hang Li 50 0 0 09 Oct 2023
DISCOVER: Making Vision Networks Interpretable via Competition and Dissection Konstantinos P. Panousis S. Chatzis 79 5 0 07 Oct 2023
Copy Suppression: Comprehensively Understanding an Attention Head Callum McDougall Arthur Conmy Cody Rushing Thomas McGrath Neel Nanda MILM 73 46 0 06 Oct 2023
Attributing Learned Concepts in Neural Networks to Training Data Nicholas Konz Charles Godfrey Madelyn Shapiro Jonathan Tu Henry Kvinge Davis Brown TDI FAtt 32 1 0 04 Oct 2023
Coarse-to-Fine Concept Bottleneck Models Konstantinos P. Panousis Dino Ienco Diego Marcos 85 8 0 03 Oct 2023
H-InDex: Visual Reinforcement Learning with Hand-Informed Representations for Dexterous Manipulation Yanjie Ze Yuyao Liu Ruizhe Shi Jiaxin Qin Zhecheng Yuan Jiashun Wang Huazhe Xu 107 1 0 02 Oct 2023
Faster and Accurate Neural Networks with Semantic Inference Sazzad Sayyed Jonathan D. Ashdown Francesco Restuccia 71 0 0 02 Oct 2023
Prototype Generation: Robust Feature Visualisation for Data Independent Interpretability Ziyin Li Bao Feng 64 1 0 29 Sep 2023
Learning to Receive Help: Intervention-Aware Concept Embedding Models M. Zarlenga Katherine M. Collins Krishnamurthy Dvijotham Adrian Weller Z. Shams M. Jamnik 91 27 0 29 Sep 2023
Explaining Deep Face Algorithms through Visualization: A Survey Thrupthi Ann S. M. I. C. V. Balasubramanian M. Jawahar CVBM 61 1 0 26 Sep 2023
FIND: A Function Description Benchmark for Evaluating Interpretability Methods Sarah Schwettmann Tamar Rott Shaham Joanna Materzyñska Neil Chowdhury Shuang Li Jacob Andreas David Bau Antonio Torralba 56 22 0 07 Sep 2023
DeViL: Decoding Vision features into Language Meghal Dani Isabel Rio-Torto Stephan Alaniz Zeynep Akata VLM 82 8 0 04 Sep 2023
Unsupervised discovery of Interpretable Visual Concepts Caroline Mazini Rodrigues Nicolas Boutry Laurent Najman FAtt 58 2 0 31 Aug 2023
Patch Is Not All You Need Chang-bo Li Jie Zhang Yang Wei Zhilong Ji Jinfeng Bai Shiguang Shan ViT 69 2 0 21 Aug 2023
Dissecting RGB-D Learning for Improved Multi-modal Fusion Hao Chen Hao Zhou Yunshu Zhang Zheng Lin Yongjian Deng 125 1 0 19 Aug 2023
Backdoor Federated Learning by Poisoning Backdoor-Critical Layers Haomin Zhuang Mingxian Yu Hao Wang Yang Hua Jian Li Xu Yuan FedML 61 15 0 08 Aug 2023
Improving Generalization of Image Captioning with Unsupervised Prompt Learning Hongchen Wei Zhenzhong Chen VLM 79 3 0 05 Aug 2023
A Multidimensional Analysis of Social Biases in Vision Transformers Jannik Brinkmann Paul Swoboda Christian Bartelt 58 8 0 03 Aug 2023
Multimodal Neurons in Pretrained Text-Only Transformers Sarah Schwettmann Neil Chowdhury Samuel J. Klein David Bau Antonio Torralba MILM 92 32 0 03 Aug 2023