On the Explainability of Natural Language Processing Deep Models

13 October 2022

Papers citing "On the Explainability of Natural Language Processing Deep Models"

10 / 10 papers shown

Title
Gender Bias in Explainability: Investigating Performance Disparity in Post-hoc Methods Mahdi Dhaini Ege Erdogan Nils Feldhus Gjergji Kasneci 21 0 0 02 May 2025
A Systematic Literature Review on Explainability for Machine/Deep Learning-based Software Engineering Research Sicong Cao Xiaobing Sun Ratnadira Widyasari David Lo Xiaoxue Wu ... Jiale Zhang Bin Li Wei Liu Di Wu Yixin Chen 8 6 0 26 Jan 2024
Power-up! What Can Generative Models Do for Human Computation Workflows? Garrett Allen Gaole He U. Gadiraju 21 3 0 05 Jul 2023
Invariant Rationalization Shiyu Chang Yang Zhang Mo Yu Tommi Jaakkola 179 197 0 22 Mar 2020
Language Models as Knowledge Bases? Fabio Petroni Tim Rocktaschel Patrick Lewis A. Bakhtin Yuxiang Wu Alexander H. Miller Sebastian Riedel KELM AI4MH 391 2,216 0 03 Sep 2019
A causal framework for explaining the predictions of black-box sequence-to-sequence models David Alvarez-Melis Tommi Jaakkola CML 210 201 0 06 Jul 2017
Methods for Interpreting and Understanding Deep Neural Networks G. Montavon Wojciech Samek K. Müller FaML 225 2,069 0 24 Jun 2017
Towards A Rigorous Science of Interpretable Machine Learning Finale Doshi-Velez Been Kim XAI FaML 219 2,098 0 28 Feb 2017
Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation Yonghui Wu M. Schuster Z. Chen Quoc V. Le Mohammad Norouzi ... Alex Rudnick Oriol Vinyals G. Corrado Macduff Hughes J. Dean AIMat 716 6,435 0 26 Sep 2016
Efficient Estimation of Word Representations in Vector Space Tomáš Mikolov Kai Chen G. Corrado J. Dean 3DV 228 29,632 0 16 Jan 2013