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

331 papers, page 4 of 7

151. ICLR 2025Non-Adversarial Inverse Reinforcement Learning via Successor Feature Matching
152. ICLR 2025On Minimizing Adversarial Counterfactual Error in Adversarial Reinforcement Learning
153. ICLR 2025Optimizing importance weighting in the presence of sub-population shifts
154. ICLR 2025PolyPythias: Stability and Outliers across Fifty Language Model Pre-Training Runs
155. ICLR 2025Provable Robust Overfitting Mitigation in Wasserstein Distributionally Robust Optimization
156. ICLR 2025Provably Reliable Conformal Prediction Sets in the Presence of Data Poisoning
157. ICLR 2025Provably Safeguarding a Classifier from OOD and Adversarial Samples
158. ICLR 2025Rethinking Invariance Regularization in Adversarial Training to Improve Robustness-Accuracy Trade-off
159. ICLR 2025Robust Feature Learning for Multi-Index Models in High Dimensions
160. ICLR 2025Robust LLM safeguarding via refusal feature adversarial training
161. ICLR 2025Robust Representation Consistency Model via Contrastive Denoising
162. ICLR 2025Robust Transfer of Safety-Constrained Reinforcement Learning Agents
163. ICLR 2025Robustness Auditing for Linear Regression: To Singularity and Beyond
164. ICLR 2025Robustness Inspired Graph Backdoor Defense
165. ICLR 2025Robustness Reprogramming for Representation Learning
166. ICLR 2025Selective Unlearning via Representation Erasure Using Domain Adversarial Training
167. ICLR 2025Shh, don't say that! Domain Certification in LLMs
168. ICLR 2025Speech Robust Bench: A Robustness Benchmark For Speech Recognition
169. ICLR 2025Stochastic Bandits Robust to Adversarial Attacks
170. ICLR 2025Strong Preferences Affect the Robustness of Preference Models and Value Alignment
171. ICLR 2025Tailoring Mixup to Data for Calibration
172. ICLR 2025Targeted Attack Improves Protection against Unauthorized Diffusion Customization
173. ICLR 2025TASAR: Transfer-based Attack on Skeletal Action Recognition
174. ICLR 2025Tight Clusters Make Specialized Experts
175. ICLR 2025To Tackle Adversarial Transferability: A Novel Ensemble Training Method with Fourier Transformation
176. ICLR 2025Towards Certification of Uncertainty Calibration under Adversarial Attacks
177. ICLR 2025Towards Scalable Topological Regularizers
178. ICLR 2025Towards Understanding the Robustness of Diffusion-Based Purification: A Stochastic Perspective
179. ICLR 2025Training Robust Ensembles Requires Rethinking Lipschitz Continuity
180. ICLR 2025Unlearn and Burn: Adversarial Machine Unlearning Requests Destroy Model Accuracy
181. ICLR 2025Verifying Properties of Binary Neural Networks Using Sparse Polynomial Optimization
182. ICLR 2025Zero-cost Proxy for Adversarial Robustness Evaluation
183. ICLR 2024A Recipe for Improved Certifiable Robustness
184. ICLR 2024A ROBUST DIFFERENTIAL NEURAL ODE OPTIMIZER
185. ICLR 2024A Sublinear Adversarial Training Algorithm
186. ICLR 2024Adversarial Attacks on Fairness of Graph Neural Networks
187. ICLR 2024Adversarial AutoMixup
188. ICLR 2024Adversarial Feature Map Pruning for Backdoor
189. ICLR 2024Adversarial Imitation Learning via Boosting
190. ICLR 2024Adversarial Training on Purification (AToP): Advancing Both Robustness and Generalization
191. ICLR 2024Adversarial Training Should Be Cast as a Non-Zero-Sum Game
192. ICLR 2024An Efficient Tester-Learner for Halfspaces
193. ICLR 2024An Image Is Worth 1000 Lies: Transferability of Adversarial Images across Prompts on Vision-Language Models
194. ICLR 2024An LLM can Fool Itself: A Prompt-Based Adversarial Attack
195. ICLR 2024Analyzing and Improving Optimal-Transport-based Adversarial Networks
196. ICLR 2024Annealing Self-Distillation Rectification Improves Adversarial Training
197. ICLR 2024AutoDAN: Generating Stealthy Jailbreak Prompts on Aligned Large Language Models
198. ICLR 2024AutoLoRa: An Automated Robust Fine-Tuning Framework
199. ICLR 2024Belief-Enriched Pessimistic Q-Learning against Adversarial State Perturbations
200. ICLR 2024Boosting the Adversarial Robustness of Graph Neural Networks: An OOD Perspective

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.