Model-tuning Via Prompts Makes NLP Models Adversarially Robust

Model-tuning Via Prompts Makes NLP Models Adversarially Robust

13 March 2023

J. Zico Kolter

Zachary Chase Lipton

Papers citing "Model-tuning Via Prompts Makes NLP Models Adversarially Robust"

11 / 11 papers shown

Title
Defending Large Language Models Against Attacks With Residual Stream Activation Analysis Amelia Kawasaki Andrew Davis Houssam Abbas AAML KELM 27 2 0 05 Jun 2024
ADAPT to Robustify Prompt Tuning Vision Transformers Masih Eskandar Tooba Imtiaz Zifeng Wang Jennifer Dy VPVLM VLM AAML 36 0 0 19 Mar 2024
Improving Few-shot Generalization of Safety Classifiers via Data Augmented Parameter-Efficient Fine-Tuning Ananth Balashankar Xiao Ma Aradhana Sinha Ahmad Beirami Yao Qin Jilin Chen Alex Beutel 16 2 0 25 Oct 2023
A Prompting-based Approach for Adversarial Example Generation and Robustness Enhancement Yuting Yang Pei Huang Juan Cao Jintao Li Yun Lin J. Dong Feifei Ma Jian Zhang AAML SILM 38 13 0 21 Mar 2022
Learning to Prompt for Vision-Language Models Kaiyang Zhou Jingkang Yang Chen Change Loy Ziwei Liu VPVLM CLIP VLM 322 2,249 0 02 Sep 2021
The Power of Scale for Parameter-Efficient Prompt Tuning Brian Lester Rami Al-Rfou Noah Constant VPVLM 280 3,835 0 18 Apr 2021
Making Pre-trained Language Models Better Few-shot Learners Tianyu Gao Adam Fisch Danqi Chen 241 1,913 0 31 Dec 2020
Exploiting Cloze Questions for Few Shot Text Classification and Natural Language Inference Timo Schick Hinrich Schütze 258 1,584 0 21 Jan 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
Certified Robustness to Adversarial Word Substitutions Robin Jia Aditi Raghunathan Kerem Göksel Percy Liang AAML 178 290 0 03 Sep 2019
Generating Natural Language Adversarial Examples M. Alzantot Yash Sharma Ahmed Elgohary Bo-Jhang Ho Mani B. Srivastava Kai-Wei Chang AAML 243 914 0 21 Apr 2018