Poster "adversarial training" Papers
62 papers found • Page 1 of 2
Conference
Accelerated Vertical Federated Adversarial Learning through Decoupling Layer-Wise Dependencies
Tianxing Man, Yu Bai, Ganyu Wang et al.
Adversarial Exploitation of Data Diversity Improves Visual Localization
Sihang Li, Siqi Tan, Bowen Chang et al.
Adversarial Generative Flow Network for Solving Vehicle Routing Problems
Ni Zhang, Jingfeng Yang, Zhiguang Cao et al.
Adversarially Robust Anomaly Detection through Spurious Negative Pair Mitigation
Hossein Mirzaei Sadeghlou, Mojtaba Nafez, Jafar Habibi et al.
ALBAR: Adversarial Learning approach to mitigate Biases in Action Recognition
Joseph Fioresi, Ishan Rajendrakumar Dave, Mubarak Shah
Algorithmic Stability Based Generalization Bounds for Adversarial Training
Runzhi Tian, Yongyi Mao
Breaking Latent Prior Bias in Detectors for Generalizable AIGC Image Detection
Yue Zhou, Xinan He, Kaiqing Lin et al.
Distributional LLM-as-a-Judge
Luyu Chen, Zeyu Zhang, Haoran Tan et al.
Generating Less Certain Adversarial Examples Improves Robust Generalization
Minxing Zhang, Michael Backes, Xiao Zhang
Improved Diffusion-based Generative Model with Better Adversarial Robustness
Zekun Wang, Mingyang Yi, Shuchen Xue et al.
Improving Generalization and Robustness in SNNs Through Signed Rate Encoding and Sparse Encoding Attacks
Bhaskar Mukhoty, Hilal AlQuabeh, Bin Gu
Indirect Gradient Matching for Adversarial Robust Distillation
Hongsin Lee, Seungju Cho, Changick Kim
Lifelong Safety Alignment for Language Models
Haoyu Wang, Yifei Zhao, Zeyu Qin et al.
Long-tailed Adversarial Training with Self-Distillation
Seungju Cho, Hongsin Lee, Changick Kim
MEIcoder: Decoding Visual Stimuli from Neural Activity by Leveraging Most Exciting Inputs
Jan Sobotka, Luca Baroni, Ján Antolík
NitroFusion: High-Fidelity Single-Step Diffusion through Dynamic Adversarial Training
Dar-Yen Chen, Hmrishav Bandyopadhyay, Kai Zou et al.
On the Alignment between Fairness and Accuracy: from the Perspective of Adversarial Robustness
Junyi Chai, Taeuk Jang, Jing Gao et al.
Out-of-Distribution Generalized Graph Anomaly Detection with Homophily-aware Environment Mixup
Sibo Tian, Xin Wang, Zeyang Zhang et al.
PBCAT: Patch-Based Composite Adversarial Training against Physically Realizable Attacks on Object Detection
Xiao Li, Yiming Zhu, Yifan Huang et al.
PN-GAIL: Leveraging Non-optimal Information from Imperfect Demonstrations
Qiang Liu, Huiqiao Fu, Kaiqiang Tang et al.
Rethinking Invariance Regularization in Adversarial Training to Improve Robustness-Accuracy Trade-off
Futa Waseda, Ching-Chun Chang, Isao Echizen
Robust LLM safeguarding via refusal feature adversarial training
Lei Yu, Virginie Do, Karen Hambardzumyan et al.
Short-length Adversarial Training Helps LLMs Defend Long-length Jailbreak Attacks: Theoretical and Empirical Evidence
Shaopeng Fu, Liang Ding, Jingfeng ZHANG et al.
Stealthy Yet Effective: Distribution-Preserving Backdoor Attacks on Graph Classification
Xiaobao Wang, Ruoxiao Sun, Yujun Zhang et al.
Towards Adversarial Robustness via Debiased High-Confidence Logit Alignment
Kejia Zhang, Juanjuan Weng, Zhiming Luo et al.
Understanding and Improving Fast Adversarial Training against $l_0$ Bounded Perturbations
Xuyang Zhong, Yixiao Huang, Chen Liu
VLMs can Aggregate Scattered Training Patches
Zhanhui Zhou, Lingjie Chen, Chao Yang et al.
ZEBRA: Towards Zero-Shot Cross-Subject Generalization for Universal Brain Visual Decoding
Haonan Wang, Jingyu Lu, Hongrui Li et al.
ACT-Diffusion: Efficient Adversarial Consistency Training for One-step Diffusion Models
Fei Kong, Jinhao Duan, Lichao Sun et al.
Adversarially Robust Deep Multi-View Clustering: A Novel Attack and Defense Framework
Haonan Huang, Guoxu Zhou, Yanghang Zheng et al.
Adversarially Robust Hypothesis Transfer Learning
Yunjuan Wang, Raman Arora
Adversarial Robustness Limits via Scaling-Law and Human-Alignment Studies
Brian Bartoldson, James Diffenderfer, Konstantinos Parasyris et al.
Benign Overfitting in Adversarial Training of Neural Networks
Yunjuan Wang, Kaibo Zhang, Raman Arora
Boosting Adversarial Training via Fisher-Rao Norm-based Regularization
Xiangyu Yin, Wenjie Ruan
Catastrophic Overfitting: A Potential Blessing in Disguise
MN Zhao, Lihe Zhang, Yuqiu Kong et al.
Collapse-Aware Triplet Decoupling for Adversarially Robust Image Retrieval
Qiwei Tian, Chenhao Lin, Zhengyu Zhao et al.
Delving into the Convergence of Generalized Smooth Minimax Optimization
Wenhan Xian, Ziyi Chen, Heng Huang
Enhancing Tracking Robustness with Auxiliary Adversarial Defense Networks
Zhewei Wu, Ruilong Yu, Qihe Liu et al.
Exploiting Supervised Poison Vulnerability to Strengthen Self-Supervised Defense
Jeremy Styborski, Mingzhi Lyu, YI HUANG et al.
Generalized Smooth Variational Inequalities: Methods with Adaptive Stepsizes
Daniil Vankov, Angelia Nedich, Lalitha Sankar
HarmBench: A Standardized Evaluation Framework for Automated Red Teaming and Robust Refusal
Mantas Mazeika, Long Phan, Xuwang Yin et al.
Improving Accuracy-robustness Trade-off via Pixel Reweighted Adversarial Training
Jiacheng Zhang, Feng Liu, Dawei Zhou et al.
Improving Adversarial Energy-Based Model via Diffusion Process
Cong Geng, Tian Han, Peng-Tao Jiang et al.
Improving Domain Generalization in Self-Supervised Monocular Depth Estimation via Stabilized Adversarial Training
Yuanqi Yao, Gang Wu, Kui Jiang et al.
Layer-Aware Analysis of Catastrophic Overfitting: Revealing the Pseudo-Robust Shortcut Dependency
Runqi Lin, Chaojian Yu, Bo Han et al.
Learning a Dynamic Privacy-preserving Camera Robust to Inversion Attacks
Jiacheng Cheng, Xiang Dai, Jia Wan et al.
Learning Differentially Private Diffusion Models via Stochastic Adversarial Distillation
Bochao Liu, Pengju Wang, Shiming Ge
Modular Learning of Deep Causal Generative Models for High-dimensional Causal Inference
Md Musfiqur Rahman, Murat Kocaoglu
On the Duality Between Sharpness-Aware Minimization and Adversarial Training
Yihao Zhang, Hangzhou He, Jingyu Zhu et al.
Preventing Catastrophic Overfitting in Fast Adversarial Training: A Bi-level Optimization Perspective
Zhaoxin Wang, Handing Wang, Cong Tian et al.