Adversarial Robustness papers, 2023–2026

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.

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

327 papers, page 4 of 7

151. ICML 2025CAT: Contrastive Adversarial Training for Evaluating the Robustness of Protective Perturbations in Latent Diffusion Models
152. ICML 2025DiffAdvMAP: Flexible Diffusion-Based Framework for Generating Natural Unrestricted Adversarial Examples
153. ICML 2025Diffusion-based Adversarial Purification from the Perspective of the Frequency Domain
154. ICML 2025Diverse Prototypical Ensembles Improve Robustness to Subpopulation Shift
155. ICML 2025Efficient Robust Conformal Prediction via Lipschitz-Bounded Networks
156. ICML 2025Enhancing Adversarial Robustness with Conformal Prediction: A Framework for Guaranteed Model Reliability
157. ICML 2025Enhancing Certified Robustness via Block Reflector Orthogonal Layers and Logit Annealing Loss
158. ICML 2025Explaining the role of Intrinsic Dimensionality in Adversarial Training
159. ICML 2025Exploring and Mitigating Adversarial Manipulation of Voting-Based Leaderboards
160. ICML 2025Generalization and Robustness of the Tilted Empirical Risk
161. ICML 2025Guardians of Image Quality: Benchmarking Defenses Against Adversarial Attacks on Image Quality Metrics
162. ICML 2025Identifying and Understanding Cross-Class Features in Adversarial Training
163. ICML 2025Improving Zero-Shot Adversarial Robustness in Vision-Language Models by Closed-form Alignment of Adversarial Path Simplices
164. ICML 2025Learning Adversarial MDPs with Stochastic Hard Constraints
165. ICML 2025Learning Gaussian DAG Models without Condition Number Bounds
166. ICML 2025Learning to Incentivize in Repeated Principal-Agent Problems with Adversarial Agent Arrivals
167. ICML 2025LEVIS: Large Exact Verifiable Input Spaces for Neural Networks
168. ICML 2025Mechanistic Unlearning: Robust Knowledge Unlearning and Editing via Mechanistic Localization
169. ICML 2025MemFreezing: A Novel Adversarial Attack on Temporal Graph Neural Networks under Limited Future Knowledge
170. ICML 2025Multi-Armed Bandits with Interference: Bridging Causal Inference and Adversarial Bandits
171. ICML 2025Near-Optimal Consistency-Robustness Trade-Offs for Learning-Augmented Online Knapsack Problems
172. ICML 2025Nearly Optimal Algorithms for Contextual Dueling Bandits from Adversarial Feedback
173. ICML 2025NeuronTune: Towards Self-Guided Spurious Bias Mitigation
174. ICML 2025Not All Wrong is Bad: Using Adversarial Examples for Unlearning
175. ICML 2025Off-Policy Actor-Critic for Adversarial Observation Robustness: Virtual Alternative Training via Symmetric Policy Evaluation
176. ICML 2025Omni-Angle Assault: An Invisible and Powerful Physical Adversarial Attack on Face Recognition
177. ICML 2025On the Adversarial Robustness of Multi-Kernel Clustering
178. ICML 2025On the Alignment between Fairness and Accuracy: from the Perspective of Adversarial Robustness
179. ICML 2025On the Clean Generalization and Robust Overfitting in Adversarial Training from Two Theoretical Views: Representation Complexity and Training Dynamics
180. ICML 2025On the Diversity of Adversarial Ensemble Learning
181. ICML 2025On the Impact of Hard Adversarial Instances on Overfitting in Adversarial Training
182. ICML 2025On the Importance of Gaussianizing Representations
183. ICML 2025On the Learnability of Distribution Classes with Adaptive Adversaries
184. ICML 2025On the Local Complexity of Linear Regions in Deep ReLU Networks
185. ICML 2025On the Tension between Byzantine Robustness and No-Attack Accuracy in Distributed Learning
186. ICML 2025One Stone, Two Birds: Enhancing Adversarial Defense Through the Lens of Distributional Discrepancy
187. ICML 2025Optimal Fair Learning Robust to Adversarial Distribution Shift
188. ICML 2025Optimizing Robustness and Accuracy in Mixture of Experts: A Dual-Model Approach
189. ICML 2025Phase and Amplitude-aware Prompting for Enhancing Adversarial Robustness
190. ICML 2025Pixel-level Certified Explanations via Randomized Smoothing
191. ICML 2025Pixel2Feature Attack (P2FA): Rethinking the Perturbed Space to Enhance Adversarial Transferability
192. ICML 2025Position: Certified Robustness Does Not (Yet) Imply Model Security
193. ICML 2025Probably Approximately Global Robustness Certification
194. ICML 2025Provably Cost-Sensitive Adversarial Defense via Randomized Smoothing
195. ICML 2025Quadratic Upper Bound for Boosting Robustness
196. ICML 2025REINFORCE Adversarial Attacks on Large Language Models: An Adaptive, Distributional, and Semantic Objective
197. ICML 2025Robust Automatic Modulation Classification with Fuzzy Regularization
198. ICML 2025RobustLight: Improving Robustness via Diffusion Reinforcement Learning for Traffic Signal Control
199. ICML 2025RobustZero: Enhancing MuZero Reinforcement Learning Robustness to State Perturbations
200. ICML 2025ROME is Forged in Adversity: Robust Distilled Datasets via Information Bottleneck

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.