Uncovering Adversarial Risks of Test-Time Adaptation

Uncovering Adversarial Risks of Test-Time Adaptation

29 January 2023

Jiachen T. Wang

Saeed Mahloujifar

Papers citing "Uncovering Adversarial Risks of Test-Time Adaptation"

13 / 13 papers shown

Title
R.I.P.: A Simple Black-box Attack on Continual Test-time Adaptation Trung-Hieu Hoang D. Vo Minh N. Do TTA AAML 84 0 0 02 Dec 2024
On the Adversarial Risk of Test Time Adaptation: An Investigation into Realistic Test-Time Data Poisoning Yongyi Su Yushu Li Nanqing Liu Kui Jia Xulei Yang Chuan-Sheng Foo Xun Xu TTA AAML 52 0 0 07 Oct 2024
MedBN: Robust Test-Time Adaptation against Malicious Test Samples Hyejin Park Jeongyeon Hwang Sunung Mun Sangdon Park Jungseul Ok AAML TTA OOD 27 5 0 28 Mar 2024
Optimization-Free Test-Time Adaptation for Cross-Person Activity Recognition Shuoyuan Wang Jindong Wang Huajun Xi Bob Zhang Lei Zhang Hongxin Wei TTA 9 11 0 28 Oct 2023
SoTTA: Robust Test-Time Adaptation on Noisy Data Streams Taesik Gong Yewon Kim Taeckyung Lee Sorn Chottananurak Sung-Ju Lee TTA 25 12 0 16 Oct 2023
A Comprehensive Survey on Test-Time Adaptation under Distribution Shifts Jian Liang R. He Tien-Ping Tan OOD VLM TTA 25 201 0 27 Mar 2023
TeST: Test-time Self-Training under Distribution Shift Samarth Sinha Peter V. Gehler Francesco Locatello Bernt Schiele TTA OOD 24 22 0 23 Sep 2022
Robustifying Vision Transformer without Retraining from Scratch by Test-Time Class-Conditional Feature Alignment Takeshi Kojima Yutaka Matsuo Yusuke Iwasawa 37 27 0 28 Jun 2022
Evaluating the Adversarial Robustness of Adaptive Test-time Defenses Francesco Croce Sven Gowal T. Brunner Evan Shelhamer Matthias Hein A. Cemgil TTA AAML 165 67 0 28 Feb 2022
Poisoning the Unlabeled Dataset of Semi-Supervised Learning Nicholas Carlini AAML 139 68 0 04 May 2021
If your data distribution shifts, use self-learning E. Rusak Steffen Schneider George Pachitariu L. Eck Peter V. Gehler Oliver Bringmann Wieland Brendel Matthias Bethge VLM OOD TTA 75 29 0 27 Apr 2021
RobustBench: a standardized adversarial robustness benchmark Francesco Croce Maksym Andriushchenko Vikash Sehwag Edoardo Debenedetti Nicolas Flammarion M. Chiang Prateek Mittal Matthias Hein VLM 207 668 0 19 Oct 2020
Domain-Adversarial Training of Neural Networks Yaroslav Ganin E. Ustinova Hana Ajakan Pascal Germain Hugo Larochelle François Laviolette M. Marchand Victor Lempitsky GAN OOD 149 9,300 0 28 May 2015