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Beyond Word Importance: Contextual Decomposition to Extract Interactions from LSTMs

16 January 2018

Papers citing "Beyond Word Importance: Contextual Decomposition to Extract Interactions from LSTMs"

25 / 125 papers shown

Title
Reverse engineering recurrent networks for sentiment classification reveals line attractor dynamics Niru Maheswaranathan Alex H. Williams Matthew D. Golub Surya Ganguli David Sussillo 81 83 0 25 Jun 2019
Incorporating Priors with Feature Attribution on Text Classification Frederick Liu Besim Avci FAtt FaML 111 120 0 19 Jun 2019
Exploring Interpretable LSTM Neural Networks over Multi-Variable Data Tian Guo Tao R. Lin Nino Antulov-Fantulin AI4TS 94 156 0 28 May 2019
Disentangled Attribution Curves for Interpreting Random Forests and Boosted Trees Summer Devlin Chandan Singh W. James Murdoch Bin Yu FAtt 62 14 0 18 May 2019
Evaluating Recurrent Neural Network Explanations L. Arras Ahmed Osman K. Müller Wojciech Samek XAI FAtt 117 88 0 26 Apr 2019
On Attribution of Recurrent Neural Network Predictions via Additive Decomposition Mengnan Du Ninghao Liu Fan Yang Shuiwang Ji Helen Zhou FAtt 71 51 0 27 Mar 2019
NeuralHydrology -- Interpreting LSTMs in Hydrology Frederik Kratzert M. Herrnegger D. Klotz Sepp Hochreiter Günter Klambauer 60 86 0 19 Mar 2019
Explaining a black-box using Deep Variational Information Bottleneck Approach Seo-Jin Bang P. Xie Heewook Lee Wei Wu Eric Xing XAI FAtt 77 77 0 19 Feb 2019
Veridical Data Science Bin Yu Karl Kumbier 104 170 0 23 Jan 2019
Interpretable machine learning: definitions, methods, and applications W. James Murdoch Chandan Singh Karl Kumbier R. Abbasi-Asl Bin Yu XAI HAI 211 1,459 0 14 Jan 2019
Analysis Methods in Neural Language Processing: A Survey Yonatan Belinkov James R. Glass 127 558 0 21 Dec 2018
Can I trust you more? Model-Agnostic Hierarchical Explanations Michael Tsang Youbang Sun Dongxu Ren Yan Liu FAtt 53 26 0 12 Dec 2018
Interpretable Deep Learning under Fire Xinyang Zhang Ningfei Wang Hua Shen S. Ji Xiapu Luo Ting Wang AAML AI4CE 138 174 0 03 Dec 2018
What can AI do for me: Evaluating Machine Learning Interpretations in Cooperative Play Shi Feng Jordan L. Boyd-Graber HAI 82 130 0 23 Oct 2018
What made you do this? Understanding black-box decisions with sufficient input subsets Brandon Carter Jonas W. Mueller Siddhartha Jain David K Gifford FAtt 90 79 0 09 Oct 2018
Improving Moderation of Online Discussions via Interpretable Neural Models Andrej Svec Matúš Pikuliak Marian Simko Maria Bielikova 40 20 0 18 Sep 2018
Interpreting Neural Networks With Nearest Neighbors Eric Wallace Shi Feng Jordan L. Boyd-Graber AAML FAtt MILM 140 54 0 08 Sep 2018
Explaining Character-Aware Neural Networks for Word-Level Prediction: Do They Discover Linguistic Rules? Fréderic Godin Kris Demuynck J. Dambre W. D. Neve T. Demeester AI4CE 82 17 0 28 Aug 2018
Dissecting Contextual Word Embeddings: Architecture and Representation Matthew E. Peters Mark Neumann Luke Zettlemoyer Wen-tau Yih 113 434 0 27 Aug 2018
Hierarchical interpretations for neural network predictions Chandan Singh W. James Murdoch Bin Yu 84 146 0 14 Jun 2018
Pathologies of Neural Models Make Interpretations Difficult Shi Feng Eric Wallace Alvin Grissom II Mohit Iyyer Pedro Rodriguez Jordan L. Boyd-Graber AAML FAtt 110 322 0 20 Apr 2018
Explanation Methods in Deep Learning: Users, Values, Concerns and Challenges Gabrielle Ras Marcel van Gerven W. Haselager XAI 116 220 0 20 Mar 2018
Learning Memory Access Patterns Milad Hashemi Kevin Swersky Jamie A. Smith Grant Ayers Heiner Litz Jichuan Chang Christos Kozyrakis Parthasarathy Ranganathan 55 207 0 06 Mar 2018
A Comparative Study of Rule Extraction for Recurrent Neural Networks Qinglong Wang Kaixuan Zhang Alexander Ororbia Masashi Sugiyama Xue Liu C. Lee Giles 86 11 0 16 Jan 2018
Detecting Statistical Interactions from Neural Network Weights Michael Tsang Dehua Cheng Yan Liu 99 193 0 14 May 2017