Impact of Adversarial Training on Robustness and Generalizability of Language Models

10 November 2022

Papers citing "Impact of Adversarial Training on Robustness and Generalizability of Language Models"

7 / 7 papers shown

Title
Exploiting the Layered Intrinsic Dimensionality of Deep Models for Practical Adversarial Training Enes Altinisik Safa Messaoud H. Sencar Hassan Sajjad Sanjay Chawla AAML 48 0 0 27 May 2024
Finding a Needle in the Adversarial Haystack: A Targeted Paraphrasing Approach For Uncovering Edge Cases with Minimal Distribution Distortion Aly M. Kassem Sherif Saad AAML 25 1 0 21 Jan 2024
Assessing Hidden Risks of LLMs: An Empirical Study on Robustness, Consistency, and Credibility Wen-song Ye Mingfeng Ou Tianyi Li Yipeng Chen Xuetao Ma ... Sai Wu Jie Fu Gang Chen Haobo Wang J. Zhao 46 36 0 15 May 2023
A3T: Accuracy Aware Adversarial Training Enes Altinisik Safa Messaoud H. Sencar Sanjay Chawla 17 6 0 29 Nov 2022
Certified Robustness to Adversarial Word Substitutions Robin Jia Aditi Raghunathan Kerem Göksel Percy Liang AAML 183 291 0 03 Sep 2019
What you can cram into a single vector: Probing sentence embeddings for linguistic properties Alexis Conneau Germán Kruszewski Guillaume Lample Loïc Barrault Marco Baroni 201 882 0 03 May 2018
Generating Natural Language Adversarial Examples M. Alzantot Yash Sharma Ahmed Elgohary Bo-Jhang Ho Mani B. Srivastava Kai-Wei Chang AAML 245 914 0 21 Apr 2018