Rationalizing Neural Predictions

13 June 2016

Papers citing "Rationalizing Neural Predictions"

50 / 193 papers shown

Title
Local Interpretations for Explainable Natural Language Processing: A Survey Siwen Luo Hamish Ivison S. Han Josiah Poon MILM 43 48 0 20 Mar 2021
Learning to Predict with Supporting Evidence: Applications to Clinical Risk Prediction Aniruddh Raghu John Guttag K. Young E. Pomerantsev Adrian Dalca Collin M. Stultz 13 9 0 04 Mar 2021
Contrastive Explanations for Model Interpretability Alon Jacovi Swabha Swayamdipta Shauli Ravfogel Yanai Elazar Yejin Choi Yoav Goldberg 44 95 0 02 Mar 2021
Explaining NLP Models via Minimal Contrastive Editing (MiCE) Alexis Ross Ana Marasović Matthew E. Peters 33 121 0 27 Dec 2020
HateXplain: A Benchmark Dataset for Explainable Hate Speech Detection Binny Mathew Punyajoy Saha Seid Muhie Yimam Chris Biemann Pawan Goyal Animesh Mukherjee 47 551 0 18 Dec 2020
AIST: An Interpretable Attention-based Deep Learning Model for Crime Prediction Yeasir Rayhan T. Hashem 24 22 0 16 Dec 2020
Learning to Rationalize for Nonmonotonic Reasoning with Distant Supervision Faeze Brahman Vered Shwartz Rachel Rudinger Yejin Choi LRM 15 42 0 14 Dec 2020
Self-Explaining Structures Improve NLP Models Zijun Sun Chun Fan Qinghong Han Xiaofei Sun Yuxian Meng Fei Wu Jiwei Li MILM XAI LRM FAtt 46 38 0 03 Dec 2020
Weakly- and Semi-supervised Evidence Extraction Danish Pruthi Bhuwan Dhingra Graham Neubig Zachary Chase Lipton 4 23 0 03 Nov 2020
Coherent Hierarchical Multi-Label Classification Networks Eleonora Giunchiglia Thomas Lukasiewicz AILaw 37 96 0 20 Oct 2020
The elephant in the interpretability room: Why use attention as explanation when we have saliency methods? Jasmijn Bastings Katja Filippova XAI LRM 54 174 0 12 Oct 2020
Why do you think that? Exploring Faithful Sentence-Level Rationales Without Supervision Max Glockner Ivan Habernal Iryna Gurevych LRM 27 25 0 07 Oct 2020
Explaining Deep Neural Networks Oana-Maria Camburu XAI FAtt 33 26 0 04 Oct 2020
Learning Variational Word Masks to Improve the Interpretability of Neural Text Classifiers Hanjie Chen Yangfeng Ji AAML VLM 15 63 0 01 Oct 2020
Can We Trust Your Explanations? Sanity Checks for Interpreters in Android Malware Analysis Ming Fan Wenying Wei Xiaofei Xie Yang Liu X. Guan Ting Liu FAtt AAML 22 36 0 13 Aug 2020
Automated Topical Component Extraction Using Neural Network Attention Scores from Source-based Essay Scoring Haoran Zhang Diane Litman 27 10 0 04 Aug 2020
Explainable Predictive Process Monitoring Musabir Musabayli F. Maggi Williams Rizzi Josep Carmona Chiara Di Francescomarino 14 60 0 04 Aug 2020
Explainable Prediction of Text Complexity: The Missing Preliminaries for Text Simplification Cristina Garbacea Mengtian Guo Samuel Carton Qiaozhu Mei 19 28 0 31 Jul 2020
BERTology Meets Biology: Interpreting Attention in Protein Language Models Jesse Vig Ali Madani L. Varshney Caiming Xiong R. Socher Nazneen Rajani 29 288 0 26 Jun 2020
Does the Whole Exceed its Parts? The Effect of AI Explanations on Complementary Team Performance Gagan Bansal Tongshuang Wu Joyce Zhou Raymond Fok Besmira Nushi Ece Kamar Marco Tulio Ribeiro Daniel S. Weld 42 583 0 26 Jun 2020
Gradient Estimation with Stochastic Softmax Tricks Max B. Paulus Dami Choi Daniel Tarlow Andreas Krause Chris J. Maddison BDL 36 85 0 15 Jun 2020
XGNN: Towards Model-Level Explanations of Graph Neural Networks Haonan Yuan Jiliang Tang Xia Hu Shuiwang Ji 34 390 0 03 Jun 2020
Rationalizing Text Matching: Learning Sparse Alignments via Optimal Transport Kyle Swanson L. Yu Tao Lei OT 29 37 0 27 May 2020
Explaining Black Box Predictions and Unveiling Data Artifacts through Influence Functions Xiaochuang Han Byron C. Wallace Yulia Tsvetkov MILM FAtt AAML TDI 23 165 0 14 May 2020
Don't Explain without Verifying Veracity: An Evaluation of Explainable AI with Video Activity Recognition Mahsan Nourani Chiradeep Roy Tahrima Rahman Eric D. Ragan Nicholas Ruozzi Vibhav Gogate AAML 15 17 0 05 May 2020
Fact or Fiction: Verifying Scientific Claims David Wadden Shanchuan Lin Kyle Lo Lucy Lu Wang Madeleine van Zuylen Arman Cohan Hannaneh Hajishirzi HAI 36 430 0 30 Apr 2020
Explainable Deep Learning: A Field Guide for the Uninitiated Gabrielle Ras Ning Xie Marcel van Gerven Derek Doran AAML XAI 41 371 0 30 Apr 2020
Towards Transparent and Explainable Attention Models Akash Kumar Mohankumar Preksha Nema Sharan Narasimhan Mitesh M. Khapra Balaji Vasan Srinivasan Balaraman Ravindran 42 99 0 29 Apr 2020
Sequential Interpretability: Methods, Applications, and Future Direction for Understanding Deep Learning Models in the Context of Sequential Data B. Shickel Parisa Rashidi AI4TS 33 17 0 27 Apr 2020
Generating Hierarchical Explanations on Text Classification via Feature Interaction Detection Hanjie Chen Guangtao Zheng Yangfeng Ji FAtt 36 92 0 04 Apr 2020
Description Based Text Classification with Reinforcement Learning Duo Chai Wei Wu Qinghong Han Fei Wu Jiwei Li VLM 121 66 0 08 Feb 2020
"Why is 'Chicago' deceptive?" Towards Building Model-Driven Tutorials for Humans Vivian Lai Han Liu Chenhao Tan 35 139 0 14 Jan 2020
On Interpretability of Artificial Neural Networks: A Survey Fenglei Fan Jinjun Xiong Mengzhou Li Ge Wang AAML AI4CE 38 300 0 08 Jan 2020
A Framework for Explainable Text Classification in Legal Document Review Christian J. Mahoney Jianping Zhang Nathaniel Huber-Fliflet Peter Gronvall Haozhen Zhao AILaw 19 32 0 19 Dec 2019
CAWA: An Attention-Network for Credit Attribution Saurav Manchanda George Karypis 14 3 0 26 Nov 2019
Domain Knowledge Aided Explainable Artificial Intelligence for Intrusion Detection and Response Sheikh Rabiul Islam W. Eberle S. Ghafoor Ambareen Siraj Mike Rogers 11 39 0 22 Nov 2019
Rethinking Cooperative Rationalization: Introspective Extraction and Complement Control Mo Yu Shiyu Chang Yang Zhang Tommi Jaakkola 21 140 0 29 Oct 2019
A Game Theoretic Approach to Class-wise Selective Rationalization Shiyu Chang Yang Zhang Mo Yu Tommi Jaakkola 22 60 0 28 Oct 2019
Human-Like Decision Making: Document-level Aspect Sentiment Classification via Hierarchical Reinforcement Learning Jingjing Wang Changlong Sun Shoushan Li Jiancheng Wang Luo Si Min Zhang Xiaozhong Liu Guodong Zhou 30 22 0 21 Oct 2019
Can I Trust the Explainer? Verifying Post-hoc Explanatory Methods Oana-Maria Camburu Eleonora Giunchiglia Jakob N. Foerster Thomas Lukasiewicz Phil Blunsom FAtt AAML 29 60 0 04 Oct 2019
Automatic Fact-guided Sentence Modification Darsh J. Shah Tal Schuster Regina Barzilay KELM 16 40 0 30 Sep 2019
KnowBias: Detecting Political Polarity in Long Text Content Aditya Saligrama 8 1 0 22 Sep 2019
Representation Learning for Electronic Health Records W. Weng Peter Szolovits 36 19 0 19 Sep 2019
Visual Interaction with Deep Learning Models through Collaborative Semantic Inference Sebastian Gehrmann Hendrik Strobelt Robert Krüger Hanspeter Pfister Alexander M. Rush HAI 21 57 0 24 Jul 2019
Evaluating Explanation Without Ground Truth in Interpretable Machine Learning Fan Yang Mengnan Du Xia Hu XAI ELM 27 66 0 16 Jul 2019
Incorporating Priors with Feature Attribution on Text Classification Frederick Liu Besim Avci FAtt FaML 31 120 0 19 Jun 2019
Model Agnostic Contrastive Explanations for Structured Data Amit Dhurandhar Tejaswini Pedapati Avinash Balakrishnan Pin-Yu Chen Karthikeyan Shanmugam Ruchi Puri FAtt 22 82 0 31 May 2019
Do Human Rationales Improve Machine Explanations? Julia Strout Ye Zhang Raymond J. Mooney 19 57 0 31 May 2019
Leveraging Latent Features for Local Explanations Ronny Luss Pin-Yu Chen Amit Dhurandhar P. Sattigeri Yunfeng Zhang Karthikeyan Shanmugam Chun-Chen Tu FAtt 49 37 0 29 May 2019
Learning Representations by Humans, for Humans Sophie Hilgard Nir Rosenfeld M. Banaji Jack Cao David C. Parkes OCL HAI AI4CE 34 29 0 29 May 2019