RoAST: Robustifying Language Models via Adversarial Perturbation with
Selective Training

RoAST: Robustifying Language Models via Adversarial Perturbation with Selective Training

7 December 2023

Madian Khabsa

Papers citing "RoAST: Robustifying Language Models via Adversarial Perturbation with Selective Training"

7 / 7 papers shown

Title
Is Fine-tuning Needed? Pre-trained Language Models Are Near Perfect for Out-of-Domain Detection Rheeya Uppaal Junjie Hu Yixuan Li OODD 117 33 0 22 May 2023
Sharpness-Aware Minimization Improves Language Model Generalization Dara Bahri H. Mobahi Yi Tay 119 97 0 16 Oct 2021
Raise a Child in Large Language Model: Towards Effective and Generalizable Fine-tuning Runxin Xu Fuli Luo Zhiyuan Zhang Chuanqi Tan Baobao Chang Songfang Huang Fei Huang LRM 136 178 0 13 Sep 2021
DynaSent: A Dynamic Benchmark for Sentiment Analysis Christopher Potts Zhengxuan Wu Atticus Geiger Douwe Kiela 227 76 0 30 Dec 2020
Calibration of Pre-trained Transformers Shrey Desai Greg Durrett UQLM 243 289 0 17 Mar 2020
FreeLB: Enhanced Adversarial Training for Natural Language Understanding Chen Zhu Yu Cheng Zhe Gan S. Sun Tom Goldstein Jingjing Liu AAML 221 436 0 25 Sep 2019
GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding Alex Jinpeng Wang Amanpreet Singh Julian Michael Felix Hill Omer Levy Samuel R. Bowman ELM 294 6,943 0 20 Apr 2018