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

334 papers, page 6 of 7

251. NeurIPS 2024Enhancing Robustness in Deep Reinforcement Learning: A Lyapunov Exponent Approach
252. NeurIPS 2024Enhancing Robustness of Graph Neural Networks on Social Media with Explainable Inverse Reinforcement Learning
253. NeurIPS 2024Enhancing Robustness of Last Layer Two-Stage Fair Model Corrections
254. NeurIPS 2024Erasing Undesirable Concepts in Diffusion Models with Adversarial Preservation
255. NeurIPS 2024Exploring Adversarial Robustness of Deep State Space Models
256. NeurIPS 2024Feature-Level Adversarial Attacks and Ranking Disruption for Visible-Infrared Person Re-identification
257. NeurIPS 2024FEEL-SNN: Robust Spiking Neural Networks with Frequency Encoding and Evolutionary Leak Factor
258. NeurIPS 2024Fight Back Against Jailbreaking via Prompt Adversarial Tuning
259. NeurIPS 2024Fine-Tuning Personalization in Federated Learning to Mitigate Adversarial Clients
260. NeurIPS 2024Full-Distance Evasion of Pedestrian Detectors in the Physical World
261. NeurIPS 2024GDeR: Safeguarding Efficiency, Balancing, and Robustness via Prototypical Graph Pruning
262. NeurIPS 2024Generate Universal Adversarial Perturbations for Few-Shot Learning
263. NeurIPS 2024GREAT Score: Global Robustness Evaluation of Adversarial Perturbation using Generative Models
264. NeurIPS 2024GuardT2I: Defending Text-to-Image Models from Adversarial Prompts
265. NeurIPS 2024High-dimensional (Group) Adversarial Training in Linear Regression
266. NeurIPS 2024If You Want to Be Robust, Be Wary of Initialization
267. NeurIPS 2024Improved Generation of Adversarial Examples Against Safety-aligned LLMs
268. NeurIPS 2024Improving Adversarial Robust Fairness via Anti-Bias Soft Label Distillation
269. NeurIPS 2024Improving Alignment and Robustness with Circuit Breakers
270. NeurIPS 2024Improving Robustness of 3D Point Cloud Recognition from a Fourier Perspective
271. NeurIPS 2024Improving robustness to corruptions with multiplicative weight perturbations
272. NeurIPS 2024Improving Subgroup Robustness via Data Selection
273. NeurIPS 2024Intrinsic Robustness of Prophet Inequality to Strategic Reward Signaling
274. NeurIPS 2024Is O(log N) practical? Near-Equivalence Between Delay Robustness and Bounded Regret in Bandits and RL
275. NeurIPS 2024JailbreakBench: An Open Robustness Benchmark for Jailbreaking Large Language Models
276. NeurIPS 2024Learning a Single Neuron Robustly to Distributional Shifts and Adversarial Label Noise
277. NeurIPS 2024Learning Bregman Divergences with Application to Robustness
278. NeurIPS 2024Learning from Uncertain Data: From Possible Worlds to Possible Models
279. NeurIPS 2024Learning-Augmented Algorithms for the Bahncard Problem
280. NeurIPS 2024MALT Powers Up Adversarial Attacks
281. NeurIPS 2024Mind the Graph When Balancing Data for Fairness or Robustness
282. NeurIPS 2024Mitigating Backdoor Attack by Injecting Proactive Defensive Backdoor
283. NeurIPS 2024Mixture of Adversarial LoRAs: Boosting Robust Generalization in Meta-Tuning
284. NeurIPS 2024Near-Optimal Dynamic Regret for Adversarial Linear Mixture MDPs
285. NeurIPS 2024No Free Lunch Theorem and Black-Box Complexity Analysis for Adversarial Optimisation
286. NeurIPS 2024No-Regret M${}^{\natural}$-Concave Function Maximization: Stochastic Bandit Algorithms and NP-Hardness of Adversarial Full-Information Setting
287. NeurIPS 2024On the Adversarial Robustness of Benjamini Hochberg
288. NeurIPS 2024On the Robustness of Spectral Algorithms for Semirandom Stochastic Block Models
289. NeurIPS 2024On the Scalability of Certified Adversarial Robustness with Generated Data
290. NeurIPS 2024On the Worst Prompt Performance of Large Language Models
291. NeurIPS 2024Online Composite Optimization Between Stochastic and Adversarial Environments
292. NeurIPS 2024Optimal Classification under Performative Distribution Shift
293. NeurIPS 2024Probabilistic Conformal Distillation for Enhancing Missing Modality Robustness
294. NeurIPS 2024Prompt-Agnostic Adversarial Perturbation for Customized Diffusion Models
295. NeurIPS 2024ProTransformer: Robustify Transformers via Plug-and-Play Paradigm
296. NeurIPS 2024Query-Based Adversarial Prompt Generation
297. NeurIPS 2024Rainbow Teaming: Open-Ended Generation of Diverse Adversarial Prompts
298. NeurIPS 2024RAMP: Boosting Adversarial Robustness Against Multiple $l_p$ Perturbations for Universal Robustness
299. NeurIPS 2024Rapid Plug-in Defenders
300. NeurIPS 2024Reconstruct and Match: Out-of-Distribution Robustness via Topological Homogeneity

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.