Adversarial Perspective

Adversarial perspective research investigates the vulnerabilities of various machine learning models, including large language models, graph neural networks, and deep reinforcement learning agents, to malicious attacks or unexpected inputs. Current research focuses on developing and evaluating adversarial attacks against these models, often employing techniques like adversarial training and exploring the transferability of attacks across different architectures. This work is crucial for enhancing the robustness and reliability of AI systems across diverse applications, ranging from improving the safety of autonomous systems to ensuring the fairness and privacy of data-driven decision-making.

Papers

September 26, 2024

An Adversarial Perspective on Machine Unlearning for AI Safety
Jakub Łucki, Boyi Wei, Yangsibo Huang, Peter Henderson, Florian Tramèr, Javier Rando
Jailbreak Attack Machine Unlearning Harmful Unlearning AI Safety Unlearning Method Adversarial Perspective

August 25, 2024

On the Robustness of Kolmogorov-Arnold Networks: An Adversarial Perspective
Tal Alter, Raz Lapid, Moshe Sipper
Native Robustness Adversarial Example Adversarial Robustness Kolmogorov Arnold Network Adversarial Scenario Adversarial Perspective White Box Adversarial Attack

August 5, 2024

Caution for the Environment: Multimodal Agents are Susceptible to Environmental Distractions
Xinbei Ma, Yiting Wang, Yao Yao, Tongxin Yuan, Aston Zhang, Zhuosheng Zhang, Hai Zhao
Environment Feature Multimodal Agent Adversarial Perspective User Interface Agent Distraction Level

August 1, 2024

Contrastive Graph Representation Learning with Adversarial Cross-view Reconstruction and Information Bottleneck
Yuntao Shou, Haozhi Lan, Xiangyong Cao
Graph Neural Network Contrastive Learning Information Bottleneck Node Representation Cross View Graph Contrastive Learning Adversarial Perspective

July 2, 2024

April 2, 2024

READ: Improving Relation Extraction from an ADversarial Perspective
Dawei Li, William Hogan, Jingbo Shang
Adversarial Attack Adversarial Training Relation Extraction Read V Level Perturbation Adversarial Perspective

February 28, 2024

Exploring Privacy and Fairness Risks in Sharing Diffusion Models: An Adversarial Perspective
Xinjian Luo, Yangfan Jiang, Fei Wei, Yuncheng Wu, Xiaokui Xiao, Beng Chin Ooi
Diffusion Model Privacy Preserving Pre Trained Diffusion Model Adversarial Perspective Fair Credit Privacy Level Property Inference Attack Fairness Attack Collaborative Diffusion Model

February 25, 2024

GreenLLaMA: A Framework for Detoxification with Explanations
Md Tawkat Islam Khondaker, Muhammad Abdul-Mageed, Laks V. S. Lakshmanan
New Framework Line by Line Explanation Parallel Corpus Adversarial Perspective Detoxification Model Fine Grained Detoxification

October 25, 2023

Symphony of experts: orchestration with adversarial insights in reinforcement learning
Matthieu Jonckheere, Chiara Mignacco, Gilles Stoltz
Reinforcement Learning Expert Knowledge Regret Bound Natural Policy Gradient Co Orchestration Adversarial Perspective

July 21, 2023

Improving Viewpoint Robustness for Visual Recognition via Adversarial Training
Shouwei Ruan, Yinpeng Dong, Hang Su, Jianteng Peng, Ning Chen, Xingxing Wei
Adversarial Training Visual Recognition Adversarial Perspective View Invariant Multi View Adversarial

July 16, 2023

Towards Viewpoint-Invariant Visual Recognition via Adversarial Training
Shouwei Ruan, Yinpeng Dong, Hang Su, Jianteng Peng, Ning Chen, Xingxing Wei
Adversarial Training Adversarial Perspective View Invariant Multi View Adversarial

June 24, 2023

Similarity Preserving Adversarial Graph Contrastive Learning
Yeonjun In, Kanghoon Yoon, Chanyoung Park
Contrastive Learning Adversarial Attack Adversarial Robustness High Similarity Adversarial Perspective Adversarial Graph Adversarial Graph Contrastive Learning

June 9, 2023

Detecting Adversarial Directions in Deep Reinforcement Learning to Make Robust Decisions
Ezgi Korkmaz, Jonah Brown-Cohen
Reinforcement Learning Adversarial Attack Deep Reinforcement Learning Adversarial Perspective Robust Decision Adversarial Direction Stable Policy

May 27, 2023

Modeling Adversarial Attack on Pre-trained Language Models as Sequential Decision Making
Xuanjie Fang, Sijie Cheng, Yang Liu, Wei Wang
Language Model Adversarial Attack Pre Trained Language Model Sequential Decision Making Adversarial Perspective

May 24, 2023

Adversarial Demonstration Attacks on Large Language Models
Jiongxiao Wang, Zichen Liu, Keun Hee Park, Zhuojun Jiang, Zhaoheng Zheng, Zhuofeng Wu, Muhao Chen, Chaowei Xiao
Large Language Model Context Learning Adversarial Perspective Unseen Validation Adversarial Demonstration

February 5, 2023

Rethinking Robust Contrastive Learning from the Adversarial Perspective
Fatemeh Ghofrani, Mehdi Yaghouti, Pooyan Jamshidi
Contrastive Learning Adversarial Training Robust Deep Adversarial Perspective Robust Contrastive Learning

October 16, 2022

Learning Self-Regularized Adversarial Views for Self-Supervised Vision Transformers
Tao Tang, Changlin Li, Guangrun Wang, Kaicheng Yu, Xiaojun Chang, Xiaodan Liang
LeArning Abstract Vision Transformer Self Supervised Learning Self Supervised Vision Transformer Adversarial Perspective

October 13, 2022

Observed Adversaries in Deep Reinforcement Learning
Eugene Lim, Harold Soh
Adversarial Attack Deep Reinforcement Learning Adversarial Perspective Monotone Adversary Deep Policy Adversary Knowledge

October 8, 2022

ViewFool: Evaluating the Robustness of Visual Recognition to Adversarial Viewpoints
Yinpeng Dong, Shouwei Ruan, Hang Su, Caixin Kang, Xingxing Wei, Jun Zhu
Native Robustness Neural Radiance Field Visual Recognition Adversarial Perspective