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 12 of 26

551. NeurIPS 2025AutoRedTeamer: Autonomous Red Teaming with Lifelong Attack Integration
552. NeurIPS 2025Backdoor Mitigation via Invertible Pruning Masks
553. NeurIPS 2025BAM-ICL: Causal Hijacking In-Context Learning with Budgeted Adversarial Manipulation
554. NeurIPS 2025Best-of-N Jailbreaking
555. NeurIPS 2025Better Language Model Inversion by Compactly Representing Next-Token Distributions
556. NeurIPS 2025Beyond $\tilde{O}(\sqrt{T})$ Constraint Violation for Online Convex Optimization with Adversarial Constraints
557. NeurIPS 2025Bits Leaked per Query: Information-Theoretic Bounds for Adversarial Attacks on LLMs
558. NeurIPS 2025Boosting Adversarial Transferability with Spatial Adversarial Alignment
559. NeurIPS 2025Bridging Symmetry and Robustness: On the Role of Equivariance in Enhancing Adversarial Robustness
560. NeurIPS 2025Broken Tokens? Your Language Model can Secretly Handle Non-Canonical Tokenizations
561. NeurIPS 2025CARES: Comprehensive Evaluation of Safety and Adversarial Robustness in Medical LLMs
562. NeurIPS 2025Certifying Deep Network Risks and Individual Predictions with PAC-Bayes Loss via Localized Priors
563. NeurIPS 2025CodeCrash: Exposing LLM Fragility to Misleading Natural Language in Code Reasoning
564. NeurIPS 2025Conformal Prediction under Lévy-Prokhorov Distribution Shifts: Robustness to Local and Global Perturbations
565. NeurIPS 2025Data Selection Matters: Towards Robust Instruction Tuning of Large Multimodal Models
566. NeurIPS 2025DenoiseRotator: Enhance Pruning Robustness for LLMs via Importance Concentration
567. NeurIPS 2025DepthVanish: Optimizing Adversarial Interval Structures for Stereo-Depth-Invisible Patches
568. NeurIPS 2025DiffBreak: Is Diffusion-Based Purification Robust?
569. NeurIPS 2025Diffusion Guided Adversarial State Perturbations in Reinforcement Learning
570. NeurIPS 2025Distributional Adversarial Attacks and Training in Deep Hedging
571. NeurIPS 2025Ditch the Denoiser: Emergence of Noise Robustness in Self-Supervised Learning from Data Curriculum
572. NeurIPS 2025Dynamic Siamese Expansion Framework for Improving Robustness in Online Continual Learning
573. NeurIPS 2025Dynamical Low-Rank Compression of Neural Networks with Robustness under Adversarial Attacks
574. NeurIPS 2025E2E-VGuard: Adversarial Prevention for Production LLM-based End-To-End Speech Synthesis
575. NeurIPS 2025Enhancing CLIP Robustness via Cross-Modality Alignment
576. NeurIPS 2025Enhancing Graph Classification Robustness with Singular Pooling
577. NeurIPS 2025Enhancing Visual Prompting through Expanded Transformation Space and Overfitting Mitigation
578. NeurIPS 2025Evaluating and Learning Optimal Dynamic Treatment Regimes under Truncation by Death
579. NeurIPS 2025Exploring Semantic-constrained Adversarial Example with Instruction Uncertainty Reduction
580. NeurIPS 2025Exploring the Noise Robustness of Online Conformal Prediction
581. NeurIPS 2025Fair Representation Learning with Controllable High Confidence Guarantees via Adversarial Inference
582. NeurIPS 2025Fit the Distribution: Cross-Image/Prompt Adversarial Attacks on Multimodal Large Language Models
583. NeurIPS 2025Fortifying Time Series: DTW-Certified Robust Anomaly Detection
584. NeurIPS 2025FrameShield: Adversarially Robust Video Anomaly Detection
585. NeurIPS 2025Generative Data Augmentation via Diffusion Distillation, Adversarial Alignment, and Importance Reweighting
586. NeurIPS 2025Harnessing the Computation Redundancy in ViTs to Boost Adversarial Transferability
587. NeurIPS 2025Heterogeneous Adversarial Play in Interactive Environments
588. NeurIPS 2025HQA-VLAttack: Towards High Quality Adversarial Attack on Vision-Language Pre-Trained Models
589. NeurIPS 2025IMPACT: Irregular Multi-Patch Adversarial Composition Based on Two‑Phase Optimization
590. NeurIPS 2025Kernel Learning with Adversarial Features: Numerical Efficiency and Adaptive Regularization
591. NeurIPS 2025Kernel von Mises Formula of the Influence Function
592. NeurIPS 2025Latent Space Factorization in LoRA
593. NeurIPS 2025Learning Robust Vision-Language Models from Natural Latent Spaces
594. NeurIPS 2025LORE: Lagrangian-Optimized Robust Embeddings for Visual Encoders
595. NeurIPS 2025MeCeFO: Enhancing LLM Training Robustness via Fault-Tolerant Optimization
596. NeurIPS 2025MIBP-Cert: Certified Training against Data Perturbations with Mixed-Integer Bilinear Programs
597. NeurIPS 2025MIP against Agent: Malicious Image Patches Hijacking Multimodal OS Agents
598. NeurIPS 2025MixAT: Combining Continuous and Discrete Adversarial Training for LLMs
599. NeurIPS 2025Multi-Environment POMDPs: Discrete Model Uncertainty Under Partial Observability
600. NeurIPS 2025Multimodal Negative Learning

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.