Making Attention Mechanisms More Robust and Interpretable with Virtual Adversarial Training

18 April 2021

Papers citing "Making Attention Mechanisms More Robust and Interpretable with Virtual Adversarial Training"

5 / 5 papers shown

Title
Black-Box Access is Insufficient for Rigorous AI Audits Stephen Casper Carson Ezell Charlotte Siegmann Noam Kolt Taylor Lynn Curtis ... Michael Gerovitch David Bau Max Tegmark David M. Krueger Dylan Hadfield-Menell AAML 34 78 0 25 Jan 2024
Improving Prediction Performance and Model Interpretability through Attention Mechanisms from Basic and Applied Research Perspectives Shunsuke Kitada FaML HAI AI4CE 32 0 0 24 Mar 2023
Improving Health Mentioning Classification of Tweets using Contrastive Adversarial Training Pervaiz Iqbal Khan Shoaib Ahmed Siddiqui Imran Razzak Andreas Dengel Sheraz Ahmed 21 3 0 03 Mar 2022
Improved Text Classification via Contrastive Adversarial Training Lin Pan Chung-Wei Hang Avirup Sil Saloni Potdar AAML 26 86 0 21 Jul 2021
A Decomposable Attention Model for Natural Language Inference Ankur P. Parikh Oscar Täckström Dipanjan Das Jakob Uszkoreit 213 1,367 0 06 Jun 2016