Defending Pre-trained Language Models as Few-shot Learners against Backdoor Attacks

23 September 2023

Papers citing "Defending Pre-trained Language Models as Few-shot Learners against Backdoor Attacks"

7 / 7 papers shown

Title
The Ultimate Cookbook for Invisible Poison: Crafting Subtle Clean-Label Text Backdoors with Style Attributes Wencong You Daniel Lowd 39 0 0 24 Apr 2025
PR-Attack: Coordinated Prompt-RAG Attacks on Retrieval-Augmented Generation in Large Language Models via Bilevel Optimization Yang Jiao Xiao Wang Kai Yang AAML SILM 35 0 0 10 Apr 2025
CleanGen: Mitigating Backdoor Attacks for Generation Tasks in Large Language Models Yuetai Li Zhangchen Xu Fengqing Jiang Luyao Niu D. Sahabandu Bhaskar Ramasubramanian Radha Poovendran SILM AAML 62 7 0 18 Jun 2024
The Power of Scale for Parameter-Efficient Prompt Tuning Brian Lester Rami Al-Rfou Noah Constant VPVLM 280 3,858 0 18 Apr 2021
Making Pre-trained Language Models Better Few-shot Learners Tianyu Gao Adam Fisch Danqi Chen 243 1,924 0 31 Dec 2020
Mitigating backdoor attacks in LSTM-based Text Classification Systems by Backdoor Keyword Identification Chuanshuai Chen Jiazhu Dai SILM 55 125 0 11 Jul 2020
Language Models as Knowledge Bases? Fabio Petroni Tim Rocktaschel Patrick Lewis A. Bakhtin Yuxiang Wu Alexander H. Miller Sebastian Riedel KELM AI4MH 440 2,588 0 03 Sep 2019