Interpreting Recurrent and Attention-Based Neural Models: a Case Study
on Natural Language Inference

Interpreting Recurrent and Attention-Based Neural Models: a Case Study on Natural Language Inference

12 August 2018

Prasad Tadepalli

Papers citing "Interpreting Recurrent and Attention-Based Neural Models: a Case Study on Natural Language Inference"

19 / 19 papers shown

Title
Hierarchical Attention Network for Interpretable ECG-based Heart Disease Classification Mario Padilla Rodriguez Mohamed Nafea 28 0 0 25 Mar 2025
Fake News Detection After LLM Laundering: Measurement and Explanation Rupak Kumar Das Jonathan Dodge 87 0 0 29 Jan 2025
A Study of the Plausibility of Attention between RNN Encoders in Natural Language Inference Duc Hau Nguyen Duc Hau Nguyen Pascale Sébillot 47 5 0 23 Jan 2025
Towards Reconciling Usability and Usefulness of Explainable AI Methodologies Pradyumna Tambwekar Matthew C. Gombolay 28 8 0 13 Jan 2023
Deconfounding Legal Judgment Prediction for European Court of Human Rights Cases Towards Better Alignment with Experts Santosh T.Y.S.S Shanshan Xu O. Ichim Matthias Grabmair 23 26 0 25 Oct 2022
Visual correspondence-based explanations improve AI robustness and human-AI team accuracy Giang Nguyen Mohammad Reza Taesiri Anh Totti Nguyen 30 42 0 26 Jul 2022
Fooling Explanations in Text Classifiers Adam Ivankay Ivan Girardi Chiara Marchiori P. Frossard AAML 22 20 0 07 Jun 2022
Controlling the Focus of Pretrained Language Generation Models Jiabao Ji Yoon Kim James R. Glass Tianxing He 27 5 0 02 Mar 2022
An empirical user-study of text-based nonverbal annotation systems for human-human conversations Joshua Y. Kim K. Yacef 14 1 0 30 Dec 2021
Interpreting Deep Learning Models in Natural Language Processing: A Review Xiaofei Sun Diyi Yang Xiaoya Li Tianwei Zhang Yuxian Meng Han Qiu Guoyin Wang Eduard H. Hovy Jiwei Li 17 44 0 20 Oct 2021
Improving the Faithfulness of Attention-based Explanations with Task-specific Information for Text Classification G. Chrysostomou Nikolaos Aletras 16 37 0 06 May 2021
Self-Explaining Structures Improve NLP Models Zijun Sun Chun Fan Qinghong Han Xiaofei Sun Yuxian Meng Fei Wu Jiwei Li MILM XAI LRM FAtt 36 38 0 03 Dec 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 23 577 0 26 Jun 2020
Generating Hierarchical Explanations on Text Classification via Feature Interaction Detection Hanjie Chen Guangtao Zheng Yangfeng Ji FAtt 28 91 0 04 Apr 2020
Explaining Explanations: Axiomatic Feature Interactions for Deep Networks Joseph D. Janizek Pascal Sturmfels Su-In Lee FAtt 27 143 0 10 Feb 2020
On Model Stability as a Function of Random Seed Pranava Madhyastha Dhruv Batra 33 61 0 23 Sep 2019
Understanding Memory Modules on Learning Simple Algorithms Kexin Wang Yu Zhou Shaonan Wang Jiajun Zhang Chengqing Zong 31 0 0 01 Jul 2019
Saliency Learning: Teaching the Model Where to Pay Attention Reza Ghaeini Xiaoli Z. Fern Hamed Shahbazi Prasad Tadepalli FAtt XAI 21 30 0 22 Feb 2019
A Decomposable Attention Model for Natural Language Inference Ankur P. Parikh Oscar Täckström Dipanjan Das Jakob Uszkoreit 201 1,367 0 06 Jun 2016