Rationale-Augmented Convolutional Neural Networks for Text Classification

14 May 2016

Papers citing "Rationale-Augmented Convolutional Neural Networks for Text Classification"

23 / 23 papers shown

Title
Going Beyond XAI: A Systematic Survey for Explanation-Guided Learning Yuyang Gao Siyi Gu Junji Jiang S. Hong Dazhou Yu Liang Zhao 29 39 0 07 Dec 2022
On the Explainability of Natural Language Processing Deep Models Julia El Zini M. Awad 29 82 0 13 Oct 2022
Aligning Eyes between Humans and Deep Neural Network through Interactive Attention Alignment Yuyang Gao Tong Sun Liang Zhao Sungsoo Ray Hong HAI 21 37 0 06 Feb 2022
What to Learn, and How: Toward Effective Learning from Rationales Samuel Carton Surya Kanoria Chenhao Tan 40 22 0 30 Nov 2021
Image Classification with Consistent Supporting Evidence Peiqi Wang Ruizhi Liao Daniel Moyer Seth Berkowitz Steven Horng Polina Golland 42 2 0 13 Nov 2021
SIM-ECG: A Signal Importance Mask-driven ECGClassification System K. Dharma Chicheng Zhang C. Gniady P. Agarwal Sushil Sharma 31 0 0 28 Oct 2021
Diagnostics-Guided Explanation Generation Pepa Atanasova J. Simonsen Christina Lioma Isabelle Augenstein LRM FAtt 38 6 0 08 Sep 2021
Improving the trustworthiness of image classification models by utilizing bounding-box annotations K. Dharma Chicheng Zhang 29 5 0 15 Aug 2021
PALRACE: Reading Comprehension Dataset with Human Data and Labeled Rationales Jiajie Zou Yuran Zhang Peiqing Jin Cheng Luo Xunyi Pan Nai Ding FaML 21 5 0 23 Jun 2021
When Can Models Learn From Explanations? A Formal Framework for Understanding the Roles of Explanation Data Peter Hase Joey Tianyi Zhou XAI 19 87 0 03 Feb 2021
Learning Variational Word Masks to Improve the Interpretability of Neural Text Classifiers Hanjie Chen Yangfeng Ji AAML VLM 13 63 0 01 Oct 2020
Rationalizing Text Matching: Learning Sparse Alignments via Optimal Transport Kyle Swanson L. Yu Tao Lei OT 29 37 0 27 May 2020
A Framework for Explainable Text Classification in Legal Document Review Christian J. Mahoney Jianping Zhang Nathaniel Huber-Fliflet Peter Gronvall Haozhen Zhao AILaw 14 32 0 19 Dec 2019
Evaluating Explanation Without Ground Truth in Interpretable Machine Learning Fan Yang Mengnan Du Xia Hu XAI ELM 27 66 0 16 Jul 2019
Interpretable Neural Predictions with Differentiable Binary Variables Jasmijn Bastings Wilker Aziz Ivan Titov 23 211 0 20 May 2019
Using Machine Learning and Natural Language Processing to Review and Classify the Medical Literature on Cancer Susceptibility Genes Yujia Bao Zhengyi Deng Yan Wang Heeyoon Kim V. D. Armengol ... Cathy Wang Giovanni Parmigiani Regina Barzilay D. Braun K. Hughes 14 43 0 24 Apr 2019
Inferring Which Medical Treatments Work from Reports of Clinical Trials Eric P. Lehman Jay DeYoung Regina Barzilay Byron C. Wallace 18 114 0 02 Apr 2019
Attention is not Explanation Sarthak Jain Byron C. Wallace FAtt 31 1,299 0 26 Feb 2019
Jointly Learning to Label Sentences and Tokens Marek Rei Anders Søgaard AI4TS 28 40 0 14 Nov 2018
JUMPER: Learning When to Make Classification Decisions in Reading Xianggen Liu Lili Mou Haotian Cui Zhengdong Lu Sen Song 32 20 0 06 Jul 2018
Right for the Right Reasons: Training Differentiable Models by Constraining their Explanations A. Ross M. C. Hughes Finale Doshi-Velez FAtt 41 582 0 10 Mar 2017
Exploiting Domain Knowledge via Grouped Weight Sharing with Application to Text Categorization Ye Zhang Matthew Lease Byron C. Wallace 10 15 0 08 Feb 2017
Aspect-augmented Adversarial Networks for Domain Adaptation Yuan Zhang Regina Barzilay Tommi Jaakkola 38 96 0 01 Jan 2017