Adversarial Robustness of Prompt-based Few-Shot Learning for Natural Language Understanding

19 June 2023

Papers citing "Adversarial Robustness of Prompt-based Few-Shot Learning for Natural Language Understanding"

9 / 9 papers shown

Title
UniGuard: Towards Universal Safety Guardrails for Jailbreak Attacks on Multimodal Large Language Models Sejoon Oh Yiqiao Jin Megha Sharma Donghyun Kim Eric Ma Gaurav Verma Srijan Kumar 71 6 0 03 Nov 2024
Exploring The Landscape of Distributional Robustness for Question Answering Models Anas Awadalla Mitchell Wortsman Gabriel Ilharco Sewon Min Ian H. Magnusson Hannaneh Hajishirzi Ludwig Schmidt ELM OOD KELM 72 19 0 22 Oct 2022
Toxicity Detection with Generative Prompt-based Inference Yau-Shian Wang Y. Chang 104 37 0 24 May 2022
Are Prompt-based Models Clueless? Pride Kavumba Ryo Takahashi Yusuke Oda VLM 144 13 0 19 May 2022
FewNLU: Benchmarking State-of-the-Art Methods for Few-Shot Natural Language Understanding Yanan Zheng Jing Zhou Yujie Qian Ming Ding Chonghua Liao Jian Li Ruslan Salakhutdinov Jie Tang Sebastian Ruder Zhilin Yang ELM 218 29 0 27 Sep 2021
The Power of Scale for Parameter-Efficient Prompt Tuning Brian Lester Rami Al-Rfou Noah Constant VPVLM 298 3,917 0 18 Apr 2021
Making Pre-trained Language Models Better Few-shot Learners Tianyu Gao Adam Fisch Danqi Chen 245 1,941 0 31 Dec 2020
Exploiting Cloze Questions for Few Shot Text Classification and Natural Language Inference Timo Schick Hinrich Schütze 261 1,601 0 21 Jan 2020
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 316 7,044 0 20 Apr 2018