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

1,290 papers, page 25 of 26

1201. NeurIPS 2023AND: Adversarial Neural Degradation for Learning Blind Image Super-Resolution
1202. NeurIPS 2023Asymmetric Certified Robustness via Feature-Convex Neural Networks
1203. NeurIPS 2023Asynchronous Proportional Response Dynamics: Convergence in Markets with Adversarial Scheduling
1204. NeurIPS 2023Balance, Imbalance, and Rebalance: Understanding Robust Overfitting from a Minimax Game Perspective
1205. NeurIPS 2023Batchnorm Allows Unsupervised Radial Attacks
1206. NeurIPS 2023Benchmarking Robustness to Adversarial Image Obfuscations
1207. NeurIPS 2023Beyond Pretrained Features: Noisy Image Modeling Provides Adversarial Defense
1208. NeurIPS 2023Blurred-Dilated Method for Adversarial Attacks
1209. NeurIPS 2023Boosting Adversarial Transferability by Achieving Flat Local Maxima
1210. NeurIPS 2023Bypassing the Simulator: Near-Optimal Adversarial Linear Contextual Bandits
1211. NeurIPS 2023CamoPatch: An Evolutionary Strategy for Generating Camoflauged Adversarial Patches
1212. NeurIPS 2023Certifiably Robust Graph Contrastive Learning
1213. NeurIPS 2023Certified Robustness via Dynamic Margin Maximization and Improved Lipschitz Regularization
1214. NeurIPS 2023Characterizing the Optimal $0-1$ Loss for Multi-class Classification with a Test-time Attacker
1215. NeurIPS 2023Color Equivariant Convolutional Networks
1216. NeurIPS 2023Connecting Certified and Adversarial Training
1217. NeurIPS 2023Content-based Unrestricted Adversarial Attack
1218. NeurIPS 2023DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models
1219. NeurIPS 2023Designing Robust Transformers using Robust Kernel Density Estimation
1220. NeurIPS 2023DiffAttack: Evasion Attacks Against Diffusion-Based Adversarial Purification
1221. NeurIPS 2023Diffusion-Based Adversarial Sample Generation for Improved Stealthiness and Controllability
1222. NeurIPS 2023Distribution Learnability and Robustness
1223. NeurIPS 2023Dynamic Regret of Adversarial Linear Mixture MDPs
1224. NeurIPS 2023Dynamically Masked Discriminator for GANs
1225. NeurIPS 2023Efficient Adversarial Contrastive Learning via Robustness-Aware Coreset Selection
1226. NeurIPS 2023Efficient Testable Learning of Halfspaces with Adversarial Label Noise
1227. NeurIPS 2023Eliminating Catastrophic Overfitting Via Abnormal Adversarial Examples Regularization
1228. NeurIPS 2023Embedding Space Interpolation Beyond Mini-Batch, Beyond Pairs and Beyond Examples
1229. NeurIPS 2023Empowering Collaborative Filtering with Principled Adversarial Contrastive Loss
1230. NeurIPS 2023Enhancing Adversarial Contrastive Learning via Adversarial Invariant Regularization
1231. NeurIPS 2023Enhancing Adversarial Robustness via Score-Based Optimization
1232. NeurIPS 2023Evaluating Robustness and Uncertainty of Graph Models Under Structural Distributional Shifts
1233. NeurIPS 2023Fantastic Robustness Measures: The Secrets of Robust Generalization
1234. NeurIPS 2023Federated Linear Bandits with Finite Adversarial Actions
1235. NeurIPS 2023Hierarchical Randomized Smoothing
1236. NeurIPS 2023HQA-Attack: Toward High Quality Black-Box Hard-Label Adversarial Attack on Text
1237. NeurIPS 2023Improving Adversarial Robustness via Information Bottleneck Distillation
1238. NeurIPS 2023Improving Adversarial Transferability via Intermediate-level Perturbation Decay
1239. NeurIPS 2023Improving Robustness with Adaptive Weight Decay
1240. NeurIPS 2023LEACE: Perfect linear concept erasure in closed form
1241. NeurIPS 2023Learning Provably Robust Estimators for Inverse Problems via Jittering
1242. NeurIPS 2023Leveraging Early-Stage Robustness in Diffusion Models for Efficient and High-Quality Image Synthesis
1243. NeurIPS 2023MADG: Margin-based Adversarial Learning for Domain Generalization
1244. NeurIPS 2023Maximization of Average Precision for Deep Learning with Adversarial Ranking Robustness
1245. NeurIPS 2023Meta-Learning Adversarial Bandit Algorithms
1246. NeurIPS 2023Multi-scale Diffusion Denoised Smoothing
1247. NeurIPS 2023Non-adversarial training of Neural SDEs with signature kernel scores
1248. NeurIPS 2023On Evaluating Adversarial Robustness of Large Vision-Language Models
1249. NeurIPS 2023On Private and Robust Bandits
1250. NeurIPS 2023On Proper Learnability between Average- and Worst-case Robustness

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.