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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A Cross Attention Approach to Diagnostic Explainability using Clinical Practice Guidelines for DepressionIEEE journal of biomedical and health informatics (IEEE JBHI), 2023 Sumit Dalal Deepa Tilwani Kaushik Roy Manas Gaur Sarika Jain V. Shalin Amit P. Sheth 164 13 0 23 Nov 2023
Labeling Neural Representations with Inverse RecognitionNeural Information Processing Systems (NeurIPS), 2023 Kirill Bykov Laura Kopf Shinichi Nakajima Matthias Kirchler Marina M.-C. Höhne BDL 427 27 0 22 Nov 2023
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Finding and Editing Multi-Modal Neurons in Pre-Trained TransformersAnnual Meeting of the Association for Computational Linguistics (ACL), 2023 Haowen Pan Yixin Cao Xiaozhi Wang Xun Yang Meng Wang KELM 268 37 0 13 Nov 2023
Towards A Unified Neural Architecture for Visual Recognition and Reasoning Calvin Luo Boqing Gong Ting Chen Chen Sun OCL ObjD 151 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 252 24 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 268 1 0 06 Nov 2023
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Explaining the Decisions of Deep Policy Networks for Robotic ManipulationsIEEE/RJS International Conference on Intelligent RObots and Systems (IROS), 2021 Seongun Kim Jaesik Choi 153 4 0 30 Oct 2023
Towards a fuller understanding of neurons with Clustered Compositional ExplanationsNeural Information Processing Systems (NeurIPS), 2023 Biagio La Rosa Leilani H. Gilpin Roberto Capobianco 202 14 0 27 Oct 2023
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Driving through the Concept Gridlock: Unraveling Explainability Bottlenecks in Automated DrivingIEEE Workshop/Winter Conference on Applications of Computer Vision (WACV), 2023 J. Echterhoff An Yan Kyungtae Han Lingxi Li Rohit Gupta Julian McAuley 220 11 0 25 Oct 2023
Corrupting Neuron Explanations of Deep Visual FeaturesIEEE International Conference on Computer Vision (ICCV), 2023 Divyansh Srivastava Tuomas P. Oikarinen Tsui-Wei Weng FAtt AAML 118 3 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 184 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 261 8 0 20 Oct 2023
Understanding Addition in Transformers Abir Harrasse Fazl Barez 562 28 0 19 Oct 2023
Frozen Transformers in Language Models Are Effective Visual Encoder Layers Ziqi Pang Ziyang Xie Yunze Man Yu-Xiong Wang 413 47 0 19 Oct 2023
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Removing Spurious Concepts from Neural Network Representations via Joint Subspace EstimationInternational Conference on Machine Learning (ICML), 2023 Floris Holstege Bram Wouters Noud van Giersbergen C. Diks 223 3 0 18 Oct 2023
From Neural Activations to Concepts: A Survey on Explaining Concepts in Neural Networks Jae Hee Lee Sergio Lanza Stefan Wermter 198 17 0 18 Oct 2023
Interpreting and Controlling Vision Foundation Models via Text Explanations Haozhe Chen Junfeng Yang Carl Vondrick Chengzhi Mao 197 8 0 16 Oct 2023
Automated Natural Language Explanation of Deep Visual Neurons with Large ModelsAAAI Conference on Artificial Intelligence (AAAI), 2023 Chenxu Zhao Wei Qian Yucheng Shi Mengdi Huai Ninghao Liu 130 5 0 16 Oct 2023
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Prototype Generation: Robust Feature Visualisation for Data Independent Interpretability Ziyin Li Bao Feng 190 2 0 29 Sep 2023
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Explaining Deep Face Algorithms through Visualization: A SurveyIEEE Transactions on Biometrics Behavior and Identity Science (TBBIS), 2023 Thrupthi Ann S. M. I. C. V. Balasubramanian M. Jawahar CVBM 227 2 0 26 Sep 2023
FIND: A Function Description Benchmark for Evaluating Interpretability MethodsNeural Information Processing Systems (NeurIPS), 2023 Sarah Schwettmann Tamar Rott Shaham Joanna Materzyñska Neil Chowdhury Shuang Li Jacob Andreas David Bau Antonio Torralba 245 31 0 07 Sep 2023
DeViL: Decoding Vision features into Language Meghal Dani Isabel Rio-Torto Stephan Alaniz Zeynep Akata VLM 179 11 0 04 Sep 2023
Unsupervised discovery of Interpretable Visual ConceptsInformation Sciences (Inf. Sci.), 2023 Caroline Mazini Rodrigues Nicolas Boutry Laurent Najman FAtt 399 3 0 31 Aug 2023
Patch Is Not All You Need Chang-bo Li Jie Zhang Yang Wei Zhilong Ji Jinfeng Bai Shiguang Shan ViT 106 3 0 21 Aug 2023
Dissecting RGB-D Learning for Improved Multi-modal Fusion Hao Chen Hao Zhou Yunshu Zhang Zheng Lin Yongjian Deng 389 1 0 19 Aug 2023
Backdoor Federated Learning by Poisoning Backdoor-Critical LayersInternational Conference on Learning Representations (ICLR), 2023 Haomin Zhuang Mingxian Yu Hao Wang Yang Hua Jian Li Xu Yuan FedML 181 27 0 08 Aug 2023

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Network Dissection: Quantifying Interpretability of Deep Visual Representations

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