Adversarial Robustness papers, 2023–2026
Adversarial examples and defenses
Scope: NeurIPS, ICLR, ICML and CVPR, 2023–2026. 1,291 papers are tagged with this topic.
Key findings
- Adversarial Robustness went from 313 papers in 2023 to 317 in 2026, roughly 1.0x in three years.
- NeurIPS publishes the most Adversarial Robustness work: 422 papers from 2023 to 2026, 33% of the four-venue total.
- The fastest-growing overlap is with Alignment and Safety: papers tagged with both rose from 13 in 2023 to 56 in 2026.
- Among the 5 topics under Security and Trust, it ranks #1 by 2026 paper count; the fastest grower in the group, Watermarking, is up 9.3x versus 1.0x here.
Papers per venue
Counts by year and venue
| Year | NeurIPS | ICLR | ICML | CVPR | Total |
|---|---|---|---|---|---|
| 2023 | 100 | 79 | 60 | 74 | 313 |
| 2024 | 131 | 70 | 73 | 60 | 334 |
| 2025 | 110 | 88 | 85 | 44 | 327 |
| 2026 | 81 | 94 | 93 | 49 | 317 |
Representative papers
Spread across years and venues so every edition shows up
- NeurIPS 2026A Little Robustness Is All You Need: Leveraging Predictions for Contextual Optimization
- ICML 2026Bias in Zeroth-Order Normal Estimation for Decision-Based Attacks
- ICLR 2026CERTIFIED VS. EMPIRICAL ADVERSARIAL ROBUSTNESS VIA HYBRID CONVOLUTIONS WITH ATTENTION STOCHASTICITY
- CVPR 2026A Combination of Noise and Bilateral Filters Achieve Supralinear and
- NeurIPS 2025A Unified Approach to Submodular Maximization Under Noise
- ICML 2025Adversarial Perturbations Are Formed by Iteratively Learning Linear Combinations of the Right Singular Vectors of the Adversarial Jacobian
- ICLR 2025$\sigma$-zero: Gradient-based Optimization of $\ell_0$-norm Adversarial Examples
- CVPR 2025A Unified, Resilient, and Explainable Adversarial Patch Detector
- NeurIPS 2024A StrongREJECT for Empty Jailbreaks
- ICML 2024Adversarial Attacks on Combinatorial Multi-Armed Bandits
- ICLR 2024An LLM can Fool Itself: A Prompt-Based Adversarial Attack
- CVPR 2024Defense Against Adversarial Attacks on No-Reference Image Quality Models with Gradient Norm Regularization
- NeurIPS 2023A Closer Look at the Robustness of Contrastive Language-Image Pre-Training (CLIP)
- ICML 2023A Law of Robustness beyond Isoperimetry
- ICLR 2023A law of adversarial risk, interpolation, and label noise
- CVPR 2023Adversarial Normalization: I Can Visualize Everything (ICE)
- NeurIPS 2026A Regularization-Based Approach to Public Belief State Search for Adversarial Games
- ICML 2026CaliDist: Calibrating Large Language Models via Behavioral Robustness to Distraction
- ICLR 2026Conformal Robustness Control: A New Strategy for Robust Decision
- CVPR 2026A Provable Energy-Guided Test-Time Defense Boosting Adversarial Robustness of Large
All Adversarial Robustness papers
79 papers, page 1 of 2
- ICLR 2023(Certified!!) Adversarial Robustness for Free!
- ICLR 2023A law of adversarial risk, interpolation, and label noise
- ICLR 2023A Unified Algebraic Perspective on Lipschitz Neural Networks
- ICLR 2023Adversarial Attacks on Adversarial Bandits
- ICLR 2023Adversarial Imitation Learning with Preferences
- ICLR 2023Adversarial Training of Self-supervised Monocular Depth Estimation against Physical-World Attacks
- ICLR 2023AGRO: Adversarial discovery of error-prone Groups for Robust Optimization
- ICLR 2023Aligning Model and Macaque Inferior Temporal Cortex Representations Improves Model-to-Human Behavioral Alignment and Adversarial Robustness
- ICLR 2023Arbitrary Virtual Try-on Network: Characteristics Representation and Trade-off between Body and Clothing
- ICLR 2023Bitrate-Constrained DRO: Beyond Worst Case Robustness To Unknown Group Shifts
- ICLR 2023Boosting Adversarial Transferability using Dynamic Cues
- ICLR 2023Brain-like representational straightening of natural movies in robust feedforward neural networks
- ICLR 2023Can CNNs Be More Robust Than Transformers?
- ICLR 2023Canary in a Coalmine: Better Membership Inference with Ensembled Adversarial Queries
- ICLR 2023Certified Defences Against Adversarial Patch Attacks on Semantic Segmentation
- ICLR 2023Certified Training: Small Boxes are All You Need
- ICLR 2023Chasing All-Round Graph Representation Robustness: Model, Training, and Optimization
- ICLR 2023Data augmentation alone can improve adversarial training
- ICLR 2023DAVA: Disentangling Adversarial Variational Autoencoder
- ICLR 2023Defending against Adversarial Audio via Diffusion Model
- ICLR 2023DensePure: Understanding Diffusion Models for Adversarial Robustness
- ICLR 2023Distributionally Robust Post-hoc Classifiers under Prior Shifts
- ICLR 2023Diversify and Disambiguate: Out-of-Distribution Robustness via Disagreement
- ICLR 2023Domain Generalisation via Domain Adaptation: An Adversarial Fourier Amplitude Approach
- ICLR 2023Efficient Certified Training and Robustness Verification of Neural ODEs
- ICLR 2023Empowering Graph Representation Learning with Test-Time Graph Transformation
- ICLR 2023Exploring and Exploiting Decision Boundary Dynamics for Adversarial Robustness
- ICLR 2023Exploring perceptual straightness in learned visual representations
- ICLR 2023Extracting Robust Models with Uncertain Examples
- ICLR 2023Finding Actual Descent Directions for Adversarial Training
- ICLR 2023Finding the Global Semantic Representation in GAN through Fréchet Mean
- ICLR 2023Fooling SHAP with Stealthily Biased Sampling
- ICLR 2023Free Lunch for Domain Adversarial Training: Environment Label Smoothing
- ICLR 2023Holistic Adversarially Robust Pruning
- ICLR 2023ILA-DA: Improving Transferability of Intermediate Level Attack with Data Augmentation
- ICLR 2023Inequality phenomenon in $l_{\infty}$-adversarial training, and its unrealized threats
- ICLR 2023Is Adversarial Training Really a Silver Bullet for Mitigating Data Poisoning?
- ICLR 2023Last Layer Re-Training is Sufficient for Robustness to Spurious Correlations
- ICLR 2023Learning MLPs on Graphs: A Unified View of Effectiveness, Robustness, and Efficiency
- ICLR 2023Localized Randomized Smoothing for Collective Robustness Certification
- ICLR 2023Making Substitute Models More Bayesian Can Enhance Transferability of Adversarial Examples
- ICLR 2023Malign Overfitting: Interpolation and Invariance are Fundamentally at Odds
- ICLR 2023Mind the Pool: Convolutional Neural Networks Can Overfit Input Size
- ICLR 2023Near-Optimal Adversarial Reinforcement Learning with Switching Costs
- ICLR 2023Near-optimal Coresets for Robust Clustering
- ICLR 2023Neural Architecture Design and Robustness: A Dataset
- ICLR 2023On Achieving Optimal Adversarial Test Error
- ICLR 2023On Explaining Neural Network Robustness with Activation Path
- ICLR 2023On the Perils of Cascading Robust Classifiers
- ICLR 2023On the Robustness of Safe Reinforcement Learning under Observational Perturbations
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FAQ
- How many Adversarial Robustness papers were published at NeurIPS, ICLR, ICML and CVPR from 2023 to 2026?
- 1,291 in total: 313 in 2023, 334 in 2024, 327 in 2025, 317 in 2026.
- How many Adversarial Robustness papers are at NeurIPS 2026?
- NeurIPS 2026 has 81 Adversarial Robustness papers, versus 110 the year before.
- How many Adversarial Robustness papers are at ICLR 2026?
- ICLR 2026 has 94 Adversarial Robustness papers, versus 88 the year before.
- How many Adversarial Robustness papers are at ICML 2026?
- ICML 2026 has 93 Adversarial Robustness papers, versus 85 the year before.
- How many Adversarial Robustness papers are at CVPR 2026?
- CVPR 2026 has 49 Adversarial Robustness papers, versus 44 the year before.
- Which conference publishes the most Adversarial Robustness papers?
- NeurIPS, with 422 papers from 2023 to 2026.