Overview

Adversarial training studies how to make models perform reliably when inputs, environments, or data distributions are deliberately or naturally shifted. A common approach alternates between finding difficult examples—using methods such as projected-gradient attacks, distributionally robust optimization, or learned attackers—and training the model to handle them; related methods target latent representations, domains, or interaction policies. These techniques are used in vision, language-model safety, detection, and reinforcement learning, with evaluations ranging from bounded perturbation benchmarks to adaptive attacks and shifted environments. A central tension is that robustness to trained or tested threats may not transfer to unseen attacks, while stronger training can cost accuracy, utility, or computation.

Latest papers

CardsList

187 papers31 papers in the last four weeks, up 121% on the four weeks before. 0.2% of all new papers.

  1. Sparse Fine-Tuning for Parameter-Efficient Adversarial Training

    Oct 29, 2026Zhaoxin Wang, Zihang Ding, Handing WangAdversarial TrainingAdversarial Robustness

  2. Adversarial Self-Distillation

    Oct 28, 2026Mohammad Sadegh Akhondzadeh, Soroush H. Zargarbashi, Aleksandar BojchevskiAdversarial Robustness of Language ModelsSafety-Preserving Fine-Tuning of Language Models

  3. A Separation Principle for Adversarial Attacks and Defense of Graph Neural Networks

    Oct 28, 2026Farid Mafi, Saber Jafarpour, Mohammad PiraniAdversarial AttacksGraph Neural Networks

  4. MANTIS: Multi-Axis News Transformations for Instance-Wise Stress Testing and Worst-Case Training in Fake News Detection

    Oct 26, 2026Dexin Liu, Fan Yang, Zimu Wang +5Fake News DetectionAdversarial Robustness

  5. Attack logics, not outputs: Concept-based Property Attacks for Shortcut Elimination in Neural Networks

    Oct 26, 2026Raik Dankworth, Felix Mächtle, Thomas Eisenbarth +1Adversarial AttacksAdversarial Robustness

  6. StaX-Net: Stackelberg Interleaved Asymmetric Network for Cross-Modality Medical Image Translation

    Oct 25, 2026Amin Golnari, Saeid SaneiImage-to-Image TranslationMedical Image Synthesis

  7. Augmentation-Guided Adversarial Training via Local Stability-Based Sample Selection

    Oct 23, 2026Daniel Agyei Asante, Mark Tetteh, Deborah Asamoah +2Adversarial TrainingAdversarial Robustness

  8. Towards Adversarially Robust Multigraph Neural Networks for Financial Crime Analysis

    Oct 22, 2026Dennis Heijmans, H. Çağrı Bilgi, Rui Wang +1Adversarial AttacksAdversarial Robustness

  9. ExGrad: Beyond Suppression - Explicit Clean-Gradient Subtraction in Adversarial Training

    Oct 21, 2026Zhiyuan Ye, Xiangyu Zhou, Ji Qi +2Adversarial TrainingAdversarial Robustness

  10. Adversarial Post-Training of Foundation Models for High-Frequency Trading

    Oct 19, 2026Alexandre Bismuth, Kang Li, Aramis Marti-Shahandeh +3Limit Order Book ModelingAdversarial Training

  11. Contrastive Adversarial Training for Robust Graph Neural Networks under Label Poisoning

    Oct 17, 2026Manshika Charvi Bissessur, Melis Ilayda Bal, Michael MuehlebachGraph Neural NetworksRobust Classification

  12. CAT-alyzing Honesty: Continuous Adversarial Training for Transferable LLM Honesty

    Oct 15, 2026Yuan-Chen Chang, Niklas Herbster, Gauthier Gidel +1LLM HonestyLLM Alignment

  13. Bias Mitigation in Audio-Enabled LLMs through Adversarial Training and Distillation Methods

    Oct 15, 2026Adnan Al Ali, Jindřich Libovický, Anne LauscherAdversarial DebiasingLanguage Model Debiasing

  14. Personalized Projected Ascent for Federated Stackelberg Optimization

    Oct 15, 2026M Yashwanth, Sharannya Ghosh, Saikiran Bulusu +1Federated LearningStochastic Gradient Descent

  15. AgentSafeEvo: Adversarial Co-Evolution for LLM Agent Safety

    Oct 14, 2026Chenxu Wang, Xiaoyu Wen, Han Qi +4LLM Agent SafetyAdversarial Training

  16. TRACER: Trace-Regularized Training Against Indirect Prompt Injection

    Oct 13, 2026Kshitij Mishra, Salem Lahlou, Nils LukasIndirect Prompt InjectionPrompt Injection Defense

  17. Adaptive Compression and Targeted Perturbation: A Unified Framework for Generalized Audio Deepfake Detection

    Oct 12, 2026Jianqiao Cui, Haoxian Zhu, Hanbiao Meng +1Audio Deepfake DetectionAudio Deepfake Detection Robustness

  18. [Re] Boosting the Visual Interpretability of CLIP via Adversarial Fine-Tuning

    Oct 10, 2026Anton Nuzhdin, Andrei Gruzitski, Balázs Egyed +1VLM InterpretabilitySaliency Map Evaluation

  19. Adversarial Gradient Forcing for Robust Few-Step Autoregressive Video Generation

    Oct 10, 2026Chenxi Xia, Yixuan Xu, Shan Liu +7Autoregressive Video GenerationLong-Horizon Video Generation

  20. When Listening Becomes Easier: Scrubbing Visual Cues for Shortcut-Free VLAs

    Oct 7, 2026Jasper Gerigk, Kenzo Aspuru-Takata, Chin-Hsuan Wu +3Vision-Language-Action ModelsRobustness of VLA Models

  21. Explaining the Saliency Map Sparsity of Adversarially-Trained Neural Networks

    Oct 7, 2026Yannick Lunk, Atell Yehor Krasnopolsky, Damien Garreau +1Adversarial TrainingGradient-Based Attribution

  22. Breaking Adversarial Transferability in Fine-Tuned Speech Recognition

    Oct 6, 2026Mojtaba Nafez, Aref Mousavi, Mohammad Ebrahim Mahdavi +3Adversarial TransferabilityAutomatic Speech Recognition

  23. AdvSim2Real : Training Web Agents Against Adaptive Prompt Injection in a Web World Model

    Oct 6, 2026Sarim Hashmi, Mukul Ranjan, Kshitij Mishra +3Adversarial TrainingSim-to-Real Transfer

  24. Improving Synthetic Data Generation for Argument Mining via Adversarial Reinforcement Learning

    Oct 6, 2026Zhijun Zhang, Qianlong Wang, Keyang Ding +5Adversarial TrainingArgument Mining

  25. Adversarial Training for Deep Hedging in Nonstationary Markets

    Oct 5, 2026Philipp J. Schneider, Lukas Looser, Antoine Garin +2Adversarial TrainingQuantitative Finance

  26. Online AutoML: Evaluating Poisoning Attacks on Cost-Utility Adversarial Training Defence Strategy for IoT Networks

    Oct 5, 2026Chukwunonso Henry Nwokoye, Khalil El-Khatib, Li YangAdversarial TrainingInternet of Things

  27. Target-free Latent Safety Alignment

    Oct 3, 2026Luoyu Chen, Weiqi Wang, Chenhan Zhang +3LLM Safety AlignmentAdversarial Robustness of Language Models