Analyzing Dynamic Adversarial Training Data in the Limit

Analyzing Dynamic Adversarial Training Data in the Limit

16 October 2021

Robin Jia

Douwe Kiela

Papers citing "Analyzing Dynamic Adversarial Training Data in the Limit"

13 / 13 papers shown

Title
Learning diverse attacks on large language models for robust red-teaming and safety tuning Seanie Lee Minsu Kim Lynn Cherif David Dobre Juho Lee ... Kenji Kawaguchi Gauthier Gidel Yoshua Bengio Nikolay Malkin Moksh Jain AAML 61 12 0 28 May 2024
How the Advent of Ubiquitous Large Language Models both Stymie and Turbocharge Dynamic Adversarial Question Generation Yoo Yeon Sung Ishani Mondal Jordan L. Boyd-Graber 28 0 0 20 Jan 2024
JAB: Joint Adversarial Prompting and Belief Augmentation Ninareh Mehrabi Palash Goyal Anil Ramakrishna Jwala Dhamala Shalini Ghosh Richard Zemel Kai-Wei Chang Aram Galstyan Rahul Gupta AAML 28 7 0 16 Nov 2023
From Adversarial Arms Race to Model-centric Evaluation: Motivating a Unified Automatic Robustness Evaluation Framework Yangyi Chen Hongcheng Gao Ganqu Cui Lifan Yuan Dehan Kong ... Longtao Huang H. Xue Zhiyuan Liu Maosong Sun Heng Ji AAML ELM 25 6 0 29 May 2023
Adversarial Training for High-Stakes Reliability Daniel M. Ziegler Seraphina Nix Lawrence Chan Tim Bauman Peter Schmidt-Nielsen ... Noa Nabeshima Benjamin Weinstein-Raun D. Haas Buck Shlegeris Nate Thomas AAML 30 59 0 03 May 2022
Models in the Loop: Aiding Crowdworkers with Generative Annotation Assistants Max Bartolo Tristan Thrush Sebastian Riedel Pontus Stenetorp Robin Jia Douwe Kiela 19 33 0 16 Dec 2021
Adversarially Constructed Evaluation Sets Are More Challenging, but May Not Be Fair Jason Phang Angelica Chen William Huang Samuel R. Bowman AAML 28 13 0 16 Nov 2021
The Perils of Using Mechanical Turk to Evaluate Open-Ended Text Generation Marzena Karpinska Nader Akoury Mohit Iyyer 209 106 0 14 Sep 2021
DynaSent: A Dynamic Benchmark for Sentiment Analysis Christopher Potts Zhengxuan Wu Atticus Geiger Douwe Kiela 230 77 0 30 Dec 2020
ANLIzing the Adversarial Natural Language Inference Dataset Adina Williams Tristan Thrush Douwe Kiela AAML 166 45 0 24 Oct 2020
Are We Modeling the Task or the Annotator? An Investigation of Annotator Bias in Natural Language Understanding Datasets Mor Geva Yoav Goldberg Jonathan Berant 239 319 0 21 Aug 2019
Hypothesis Only Baselines in Natural Language Inference Adam Poliak Jason Naradowsky Aparajita Haldar Rachel Rudinger Benjamin Van Durme 190 576 0 02 May 2018
Adversarial Example Generation with Syntactically Controlled Paraphrase Networks Mohit Iyyer John Wieting Kevin Gimpel Luke Zettlemoyer AAML GAN 187 711 0 17 Apr 2018