Explaining Natural Language Processing Classifiers with Occlusion and Language Modeling

28 January 2021

Papers citing "Explaining Natural Language Processing Classifiers with Occlusion and Language Modeling"

50 / 64 papers shown

Title
Generative Adversarial Networks Gilad Cohen Raja Giryes GAN 298 30,150 0 01 Mar 2022
Considering Likelihood in NLP Classification Explanations with Occlusion and Language Modeling David Harbecke Christoph Alt 52 10 0 21 Apr 2020
End-to-end ASR: from Supervised to Semi-Supervised Learning with Modern Architectures Gabriel Synnaeve Qiantong Xu Jacob Kahn Tatiana Likhomanenko Edouard Grave Vineel Pratap Anuroop Sriram Vitaliy Liptchinsky R. Collobert SSL AI4TS 117 247 0 19 Nov 2019
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer Colin Raffel Noam M. Shazeer Adam Roberts Katherine Lee Sharan Narang Michael Matena Yanqi Zhou Wei Li Peter J. Liu AIMat 485 20,342 0 23 Oct 2019
Attention is not not Explanation Sarah Wiegreffe Yuval Pinter XAI AAML FAtt 122 914 0 13 Aug 2019
StructBERT: Incorporating Language Structures into Pre-training for Deep Language Understanding Wei Wang Bin Bi Ming Yan Chen Henry Wu Zuyi Bao Jiangnan Xia Liwei Peng Luo Si 62 264 0 13 Aug 2019
RoBERTa: A Robustly Optimized BERT Pretraining Approach Yinhan Liu Myle Ott Naman Goyal Jingfei Du Mandar Joshi Danqi Chen Omer Levy M. Lewis Luke Zettlemoyer Veselin Stoyanov AIMat 686 24,557 0 26 Jul 2019
XLNet: Generalized Autoregressive Pretraining for Language Understanding Zhilin Yang Zihang Dai Yiming Yang J. Carbonell Ruslan Salakhutdinov Quoc V. Le AI4CE 236 8,451 0 19 Jun 2019
Adversarial Examples Are Not Bugs, They Are Features Andrew Ilyas Shibani Santurkar Dimitris Tsipras Logan Engstrom Brandon Tran Aleksander Madry SILM 93 1,845 0 06 May 2019
Full-Gradient Representation for Neural Network Visualization Suraj Srinivas François Fleuret MILM FAtt 77 276 0 02 May 2019
SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systems Alex Jinpeng Wang Yada Pruksachatkun Nikita Nangia Amanpreet Singh Julian Michael Felix Hill Omer Levy Samuel R. Bowman ELM 274 2,323 0 02 May 2019
Linguistic Knowledge and Transferability of Contextual Representations Nelson F. Liu Matt Gardner Yonatan Belinkov Matthew E. Peters Noah A. Smith 137 735 0 21 Mar 2019
Attention is not Explanation Sarthak Jain Byron C. Wallace FAtt 148 1,329 0 26 Feb 2019
Right for the Wrong Reasons: Diagnosing Syntactic Heuristics in Natural Language Inference R. Thomas McCoy Ellie Pavlick Tal Linzen 143 1,244 0 04 Feb 2019
Verb Argument Structure Alternations in Word and Sentence Embeddings Katharina Kann Alex Warstadt Adina Williams Samuel R. Bowman 51 50 0 27 Nov 2018
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding Jacob Devlin Ming-Wei Chang Kenton Lee Kristina Toutanova VLM SSL SSeg 1.8K 95,229 0 11 Oct 2018
Sanity Checks for Saliency Maps Julius Adebayo Justin Gilmer M. Muelly Ian Goodfellow Moritz Hardt Been Kim FAtt AAML XAI 150 1,970 0 08 Oct 2018
Generalisation in humans and deep neural networks Robert Geirhos Carlos R. Medina Temme Jonas Rauber Heiko H. Schutt Matthias Bethge Felix Wichmann OOD 107 610 0 27 Aug 2018
SentencePiece: A simple and language independent subword tokenizer and detokenizer for Neural Text Processing Taku Kudo John Richardson 206 3,531 0 19 Aug 2018
Neural Network Acceptability Judgments Alex Warstadt Amanpreet Singh Samuel R. Bowman 242 1,413 0 31 May 2018
Morphosyntactic Tagging with a Meta-BiLSTM Model over Context Sensitive Token Encodings Bernd Bohnet Ryan T. McDonald Gonçalo Simões D. Andor Emily Pitler Joshua Maynez AI4CE 53 95 0 21 May 2018
GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding Alex Jinpeng Wang Amanpreet Singh Julian Michael Felix Hill Omer Levy Samuel R. Bowman ELM 1.1K 7,200 0 20 Apr 2018
Deep contextualized word representations Matthew E. Peters Mark Neumann Mohit Iyyer Matt Gardner Christopher Clark Kenton Lee Luke Zettlemoyer NAI 233 11,565 0 15 Feb 2018
A Survey Of Methods For Explaining Black Box Models Riccardo Guidotti A. Monreale Salvatore Ruggieri Franco Turini D. Pedreschi F. Giannotti XAI 146 3,979 0 06 Feb 2018
A Human-Grounded Evaluation Benchmark for Local Explanations of Machine Learning Sina Mohseni Jeremy E. Block Eric D. Ragan FAtt XAI 82 61 0 16 Jan 2018
Interpretability Beyond Feature Attribution: Quantitative Testing with Concept Activation Vectors (TCAV) Been Kim Martin Wattenberg Justin Gilmer Carrie J. Cai James Wexler F. Viégas Rory Sayres FAtt 232 1,850 0 30 Nov 2017
The (Un)reliability of saliency methods Pieter-Jan Kindermans Sara Hooker Julius Adebayo Maximilian Alber Kristof T. Schütt Sven Dähne D. Erhan Been Kim FAtt XAI 106 688 0 02 Nov 2017
Counterfactual Explanations without Opening the Black Box: Automated Decisions and the GDPR Sandra Wachter Brent Mittelstadt Chris Russell MLAU 129 2,366 0 01 Nov 2017
Interpretable Convolutional Neural Networks Quanshi Zhang Ying Nian Wu Song-Chun Zhu FAtt 74 784 0 02 Oct 2017
The Expressive Power of Neural Networks: A View from the Width Zhou Lu Hongming Pu Feicheng Wang Zhiqiang Hu Liwei Wang 99 899 0 08 Sep 2017
Universal Function Approximation by Deep Neural Nets with Bounded Width and ReLU Activations Boris Hanin 62 356 0 09 Aug 2017
A causal framework for explaining the predictions of black-box sequence-to-sequence models David Alvarez-Melis Tommi Jaakkola CML 359 204 0 06 Jul 2017
Methods for Interpreting and Understanding Deep Neural Networks G. Montavon Wojciech Samek K. Müller FaML 293 2,267 0 24 Jun 2017
Explanation in Artificial Intelligence: Insights from the Social Sciences Tim Miller XAI 252 4,281 0 22 Jun 2017
Attention Is All You Need Ashish Vaswani Noam M. Shazeer Niki Parmar Jakob Uszkoreit Llion Jones Aidan Gomez Lukasz Kaiser Illia Polosukhin 3DV 792 132,454 0 12 Jun 2017
Learning how to explain neural networks: PatternNet and PatternAttribution Pieter-Jan Kindermans Kristof T. Schütt Maximilian Alber K. Müller D. Erhan Been Kim Sven Dähne XAI FAtt 79 341 0 16 May 2017
A Broad-Coverage Challenge Corpus for Sentence Understanding through Inference Adina Williams Nikita Nangia Samuel R. Bowman 524 4,497 0 18 Apr 2017
Interpretable Explanations of Black Boxes by Meaningful Perturbation Ruth C. Fong Andrea Vedaldi FAtt AAML 76 1,525 0 11 Apr 2017
Learning Important Features Through Propagating Activation Differences Avanti Shrikumar Peyton Greenside A. Kundaje FAtt 203 3,883 0 10 Apr 2017
Axiomatic Attribution for Deep Networks Mukund Sundararajan Ankur Taly Qiqi Yan OOD FAtt 193 6,024 0 04 Mar 2017
Opening the Black Box of Deep Neural Networks via Information Ravid Shwartz-Ziv Naftali Tishby AI4CE 113 1,416 0 02 Mar 2017
Towards A Rigorous Science of Interpretable Machine Learning Finale Doshi-Velez Been Kim XAI FaML 408 3,820 0 28 Feb 2017
Visualizing Deep Neural Network Decisions: Prediction Difference Analysis L. Zintgraf Taco S. Cohen T. Adel Max Welling FAtt 143 708 0 15 Feb 2017
"What is Relevant in a Text Document?": An Interpretable Machine Learning Approach L. Arras F. Horn G. Montavon K. Müller Wojciech Samek 69 288 0 23 Dec 2016
Assessing the Ability of LSTMs to Learn Syntax-Sensitive Dependencies Tal Linzen Emmanuel Dupoux Yoav Goldberg 108 906 0 04 Nov 2016
Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation Yonghui Wu M. Schuster Zhiwen Chen Quoc V. Le Mohammad Norouzi ... Alex Rudnick Oriol Vinyals G. Corrado Macduff Hughes J. Dean AIMat 911 6,797 0 26 Sep 2016
Enriching Word Vectors with Subword Information Piotr Bojanowski Edouard Grave Armand Joulin Tomas Mikolov NAI SSL VLM 232 9,980 0 15 Jul 2016
Charagram: Embedding Words and Sentences via Character n-grams John Wieting Joey Tianyi Zhou Kevin Gimpel Karen Livescu NAI GNN 159 193 0 10 Jul 2016
European Union regulations on algorithmic decision-making and a "right to explanation" B. Goodman Seth Flaxman FaML AILaw 67 1,903 0 28 Jun 2016
The Mythos of Model Interpretability Zachary Chase Lipton FaML 183 3,708 0 10 Jun 2016