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

313 papers, page 3 of 7

101. ICLR 2023Exploring and Exploiting Decision Boundary Dynamics for Adversarial Robustness
102. ICLR 2023Exploring perceptual straightness in learned visual representations
103. ICLR 2023Extracting Robust Models with Uncertain Examples
104. ICLR 2023Finding Actual Descent Directions for Adversarial Training
105. ICLR 2023Finding the Global Semantic Representation in GAN through Fréchet Mean
106. ICLR 2023Fooling SHAP with Stealthily Biased Sampling
107. ICLR 2023Free Lunch for Domain Adversarial Training: Environment Label Smoothing
108. ICLR 2023Holistic Adversarially Robust Pruning
109. ICLR 2023ILA-DA: Improving Transferability of Intermediate Level Attack with Data Augmentation
110. ICLR 2023Inequality phenomenon in $l_{\infty}$-adversarial training, and its unrealized threats
111. ICLR 2023Is Adversarial Training Really a Silver Bullet for Mitigating Data Poisoning?
112. ICLR 2023Last Layer Re-Training is Sufficient for Robustness to Spurious Correlations
113. ICLR 2023Learning MLPs on Graphs: A Unified View of Effectiveness, Robustness, and Efficiency
114. ICLR 2023Localized Randomized Smoothing for Collective Robustness Certification
115. ICLR 2023Making Substitute Models More Bayesian Can Enhance Transferability of Adversarial Examples
116. ICLR 2023Malign Overfitting: Interpolation and Invariance are Fundamentally at Odds
117. ICLR 2023Mind the Pool: Convolutional Neural Networks Can Overfit Input Size
118. ICLR 2023Near-Optimal Adversarial Reinforcement Learning with Switching Costs
119. ICLR 2023Near-optimal Coresets for Robust Clustering
120. ICLR 2023Neural Architecture Design and Robustness: A Dataset
121. ICLR 2023On Achieving Optimal Adversarial Test Error
122. ICLR 2023On Explaining Neural Network Robustness with Activation Path
123. ICLR 2023On the Perils of Cascading Robust Classifiers
124. ICLR 2023On the Robustness of Safe Reinforcement Learning under Observational Perturbations
125. ICLR 2023One-Pixel Shortcut: On the Learning Preference of Deep Neural Networks
126. ICLR 2023Part-Based Models Improve Adversarial Robustness
127. ICLR 2023Probabilistically Robust Recourse: Navigating the Trade-offs between Costs and Robustness in Algorithmic Recourse
128. ICLR 2023Prompting GPT-3 To Be Reliable
129. ICLR 2023Provable Defense Against Geometric Transformations
130. ICLR 2023Provable Robustness against Wasserstein Distribution Shifts via Input Randomization
131. ICLR 2023Provably Auditing Ordinary Least Squares in Low Dimensions
132. ICLR 2023Pushing the Accuracy-Group Robustness Frontier with Introspective Self-play
133. ICLR 2023Rethinking the Effect of Data Augmentation in Adversarial Contrastive Learning
134. ICLR 2023Revisiting adapters with adversarial training
135. ICLR 2023Revisiting Graph Adversarial Attack and Defense From a Data Distribution Perspective
136. ICLR 2023Revisiting Robustness in Graph Machine Learning
137. ICLR 2023Robust Algorithms on Adaptive Inputs from Bounded Adversaries
138. ICLR 2023Robust Explanation Constraints for Neural Networks
139. ICLR 2023Robust Multivariate Time-Series Forecasting: Adversarial Attacks and Defense Mechanisms
140. ICLR 2023Robustness to corruption in pre-trained Bayesian neural networks
141. ICLR 2023Sound Randomized Smoothing in Floating-Point Arithmetic
142. ICLR 2023Squeeze Training for Adversarial Robustness
143. ICLR 2023TextGrad: Advancing Robustness Evaluation in NLP by Gradient-Driven Optimization
144. ICLR 2023TextShield: Beyond Successfully Detecting Adversarial Sentences in text classification
145. ICLR 2023The Asymmetric Maximum Margin Bias of Quasi-Homogeneous Neural Networks
146. ICLR 2023The Lazy Neuron Phenomenon: On Emergence of Activation Sparsity in Transformers
147. ICLR 2023Toward Adversarial Training on Contextualized Language Representation
148. ICLR 2023Towards Robustness Certification Against Universal Perturbations
149. ICLR 2023Transferable Unlearnable Examples
150. ICLR 2023Truncated Diffusion Probabilistic Models and Diffusion-based Adversarial Auto-Encoders

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.