Attention Meets Perturbations: Robust and Interpretable Attention with Adversarial Training

25 September 2020

Papers citing "Attention Meets Perturbations: Robust and Interpretable Attention with Adversarial Training"

9 / 9 papers shown

Title
SATO: Stable Text-to-Motion Framework Wenshuo Chen Hongru Xiao Erhang Zhang Lijie Hu Lei Wang Mengyuan Liu Chong Chen 47 5 0 02 May 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
COmic: Convolutional Kernel Networks for Interpretable End-to-End Learning on (Multi-)Omics Data Jonas C. Ditz Bernhard Reuter Nícolas Pfeifer 29 1 0 02 Dec 2022
SEAT: Stable and Explainable Attention Lijie Hu Yixin Liu Ninghao Liu Mengdi Huai Lichao Sun Di Wang OOD 32 18 0 23 Nov 2022
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
Making Attention Mechanisms More Robust and Interpretable with Virtual Adversarial Training Shunsuke Kitada Hitoshi Iyatomi AAML 28 8 0 18 Apr 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
Effective Approaches to Attention-based Neural Machine Translation Thang Luong Hieu H. Pham Christopher D. Manning 218 7,926 0 17 Aug 2015