Adversarial Examples

Latest papers 57

4 papers in the last four weeks, down 60% on the four weeks before. 0.0% of all new papers.

Collaboratively Guided Adversarial Robust Distillation with Teacher-Favorable Examples
Oct 8, 2026Zhi Li, Haowei Liu, Hongchen Yang +4Adversarial Robustness Adversarial Knowledge Distillation
Engineering Research Center of Cyberspace and School of Software and AI, Yunnan University, Kunming, China · School of Information Science and Technology, Yunnan Normal University, Kunming, China
SPIN: Image Immunization Against Diffusion Editing via Single-Step Projection in Stochastic Neighborhoods
Oct 5, 2026Fengming Gu, Jie Zhang, Zhongqi Wang +3Adversarial Examples Diffusion-Based Image Editing
School of Advanced Interdisciplinary Sciences, University of Chinese Academy of Sciences · State Key Laboratory of AI Safety, Institute of Computing Technology, Chinese Academy of Sciences · University of Chinese Academy of Sciences +1
Anti-Persona: Disrupting Unauthorized Identity Binding and Recognition in Personalized Vision--Language Models
Oct 1, 2026Abhishek Basu, Fahad Shamshad, Karthik NandakumarVLM Robustness Vision-Language Models
MBZUAI, UAE · Michigan State University, USA
CollageAttack: Exploiting Cross-Modal Alignment Flaws in T2I Models through Spatial Text Composition
Sep 29, 2026Zhiyi Mou, Yao Lu, Wangze Ni +6Adversarial Examples Vision-Language Alignment
Zhejiang University · Hong Kong Polytechnic University
Evaluating the Semantic-to-Geometric Gap in Adversarial Defenses Against Vision-Language Model-Based Plagiarism
Sep 22, 2026Christopher Burger, Christina Trotter, Joseph Carlisle +1VLM Robustness Adversarial Attacks on VLMs
Pelican Quantitative · The University of Mississippi
Discovering Natural Transformation Vulnerabilities in Black-Box Vision Models
Sep 7, 2026Dongsu Song, DaeYun GO, Jay Hoon JungAdversarial Attacks Adversarial Examples
Generating Adversarial Texts for Machine Translation via GRPO
Sep 5, 2026Florian Zogaj, Jakob Hütteneder, Giovanni De Muri +3Adversarial Examples
ETH Zurich, Switzerland
Audio-Driven Adversarial Defense for 3D Talking Face Generation with totally Visual Fidelity Preservation
Aug 31, 2026Rui-Qing Sun, Chen-Hao Cui, Hui-Yang Zhao +3Audio-Driven Facial Animation Adversarial Examples
Beijing Institute of Technology Haidian Qu, Beijing Shi, China
Adversarial Training Without Input Gradients via Low-Rank Householder Expansions
Aug 27, 2026Tiana C. Johnson, Donsub RimAdversarial Training Adversarial Robustness
Multi2AV-Safety: Benchmarking Safety in Multimodal-to-Audio-Video Generation
Aug 27, 2026Kaichao Jiang, Changtao Miao, Baiqi Wu +8Audio-Video Generation Multimodal Generation
University of Science and Technology of China · Independent Researcher · Zhejiang University +1
Why Does Robustness Reduce Superposition?
Aug 23, 2026Adam ElimadiFeature Superposition Adversarial Examples
Independent Researcher
GuardPaint:SpeculativeSafetyDecodingforText-to-ImageGeneration
Aug 22, 2026Shreyash Dhoot, Paras Dhiman, Arsh Abbas Naqvi +4Safe T2I Generation Adversarial Examples
Pragya Lab, BITS Pilani Goa, India · Apple, USA · Meta, USA
ArmorOCR: Grounded Adversarial Visual Perception via Observation-Transferred Self-Distillation
Aug 20, 2026Linhan Cao, Siyuan Li, Jun Lan +8Adversarial Robustness Adversarial Examples
Training-Free Reconstruction-Based AI-Generated Image Detectors Are Inherently Vulnerable to Adversarial Examples
Aug 17, 2026Roman Demchenko, Jonas Ricker, Asja FischerAI-Generated Image Detection Adversarial Attacks
Augmenting Text to Increase Translation Difficulty
Aug 16, 2026William Kalikman, Šimon Sukup, Michal Tešnar +1MT Evaluation Adversarial Examples
SPARED: Reasoning-Based AI-Generated Image Detection via Adversarially Edited Data
Aug 13, 2026Yicheng Bao, Xiahui Guo, Xuhong Wang +1Adversarial Training Adversarial Examples
1East China Normal University · 2Shanghai Artificial Intelligence Laboratory
SRAP: SVD-Refined Adversarial Perturbations for Imperceptible Face-Swap Defense
Aug 4, 2026Sungwon Cho, Kwanghyun Ko, Myungjoo KangAdversarial Examples Adversarial Perturbations
Interdisciplinary Program in Artificial Intelligence Seoul National University · Interdisciplinary Program in Computational Science and Technology Seoul National University · Department of Mathematical Sciences Seoul National University
VETO: Towards Protecting Images From Frontier AI Editing
Jul 29, 2026Jonas Grebe, Hossein Shakibania, Tobias Braun +2Image Editing Evaluation Adversarial Examples
TU Darmstadt & hessian.AI, Germany · Zuse School ELIZA
InkShield: Writing Style Protection Against Unauthorized Handwriting Mimicry
Jul 29, 2026Jian Xiong, Wenbo Jiang, Zihan Wang +4Adversarial Examples
University of Electronic Science and Technology of China
I2VShield: An Efficient Proactive Defense Framework against DiT-based Image-to-Video Models
Jul 28, 2026Yimao Guo, Zuomin Qu, Wei LuImage-to-Video Generation Adversarial Attacks
School of Computer Science and Engineering, Sun Yat-sen University Ministry of Education Key Laboratory of Information Technology Guangdong Province Key Laboratory of Information Security Technology Guangzhou 510006, China · Guangdong Province Key Laboratory of Information Security Technology Guangzhou 510006, China · State Key Laboratory of HVDC, China Southern Power Grid Electric Power Research Institute
ISPCloak: Weaponizing ISP for Optimization-Free Physical Camouflage against Deepfake Detectors
Jul 24, 2026Jiale Zhao, Jiajun Wan, Lei Tang +3Adversarial Attacks Deepfake Detection
Guangdong University of Technology Guangzhou, China · Guizhou Provincial Laboratory of Big Data, State Key Laboratory of Public Big Data, Guizhou University Guiyang, China
A New Kind of Adversarial Example: Measuring the Human-Model Gap, and Its Relationship to OOD Detection
Jul 22, 2026Ali BorjiAdversarial Robustness Adversarial Examples
BrainChip Inc., Laguna Hills, CA, USA
Dynamic Defense Profiling Enables Cognitive Jailbreak of Text-to-Image Models
Jul 20, 2026Dongdong Yang, Deyue Zhang, Zhao Liu +5Adversarial Prompt Generation Adversarial Examples
AI Security Lab, Beijing, China · School of Artificial Intelligence, Beihang University, Beijing, China
Semantic Color Naturalness Breaker: Preventing Illegitimate Colorization via Content-Aware Color Priors
Jul 20, 2026Yuki Nii, Futa Waseda, Ching-Chun Chang +1Adversarial Examples
The University of Tokyo, Japan · National Institute of Informatics, Japan
Automatic Hard Example Synthesis with Multi-Level Agentic Data Curation
Jul 15, 2026Genglin Liu, Muye Zhang, Krishnamurthy Viswanathan +5Multimodal Robustness Adversarial Scenario Generation
1UCLA · *Work done as a student researcher at Google. · 2Google
DiffUE: Enhancing Utility-Unlearnability Trade-off of Unlearnable Examples via Diffusion Autoencoders
Jul 12, 2026Syed Irfan Ali Meerza, Oktay Ozturk, Amir Sadovnik +1Adversarial Examples Privacy-Preserving ML
University of Tennessee, Knoxville, TN, USA · Virginia Commonwealth University, Richmond, VA, USA · Oak Ridge National University, Knoxville, TN, USA +1
Imperceptible and Reversible Adversarial Examples against Vision-Language Models for Privacy Protection
Jul 11, 2026Qi Lu, Ziqi Zhou, Yufei Song +5VLM Robustness Adversarial Attacks on VLMs
School of Cyber Science and Engineering, Huazhong University of Science and Technology · College of Computer Science, Chongqing University · School of Software and engineering, Huazhong University of Science and Technology +2
Statistically Undetectable Backdoors in Deep Neural Networks
Jul 10, 2026Andrej Bogdanov, Alon Rosen, Neekon VafaBackdoor Attacks Adversarial Examples
University of Ottawa. · Bocconi University. · Massachusetts Institute of Technology.
Adversarially Guided Diffusion for LiDAR Range Image Synthesis
Jul 8, 2026Stavros Bouras, Antonios Makris, Alexandros Gkillas +2Adversarial Attacks Adversarial Examples
School of Electrical and Computer Engineering, National Technical University of Athens, Greece · Industrial Systems Institute, Athena Research Center, Patras Science Park, Greece
Unlearnable Faces: Privacy Protection Surviving Extraction Pipeline
Jul 7, 2026Byunghoon Oh, Sunghwan Park, Jaewoo LeeAdversarial Examples Privacy-Preserving ML
Chung-Ang University, Seoul, South Korea

Oct 8, 2026, cs.CVJ/K move · Enter open · S save

Collaboratively Guided Adversarial Robust Distillation with Teacher-Favorable Examples

Zhi Li, Haowei Liu, Hongchen Yang, Xiaoxuan Wang+3

Engineering Research Center of Cyberspace and School of Software and AI, Yunnan University, Kunming, China · School of Information Science and Technology, Yunnan Normal University, Kunming, China

Adversarial Robustness Adversarial Knowledge Distillation Adversarial Examples

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Adversarial distillation transfers robustness from high-capacity teachers to compact students. Existing adversarial distillation methods mainly use teacher predictions on clean or adversarial examples to supervise student learning. However, teacher-favorable supervision within the perturbation neighborhood remains underexplored in adversarial distillation. We therefore propose Collaboratively Guided Adversarial Robust Distillation (CGARD), which jointly optimizes distinct student-adversarial and teacher-collaborative examples within the same perturbation neighborhood. The teacher-collaborative example is constrained to incur no greater cross-entropy loss under the teacher than the clean input. CGARD combines collaborative teacher guidance with adversarial teacher supervision to improve robust knowledge transfer. Experiments on CIFAR-10 and CIFAR-100, including white-box evaluation and additional black-box transfer evaluation, demonstrate consistent robustness improvements over strong adversarial distillation baselines.