Adversarial Robustness papers, 2023–2026

Adversarial examples and defenses

Scope: NeurIPS, ICLR, ICML and CVPR, 2023–2026. 1,291 papers are tagged with this topic.

Key findings

Papers per year

Papers per venue

Counts by year and venue

Adversarial Robustness papers by year and venue
YearNeurIPSICLRICMLCVPRTotal
2023100796074313
2024131707360334
2025110888544327
202681949349317

Representative papers

Spread across years and venues so every edition shows up

All Adversarial Robustness papers

1,290 papers, page 26 of 26

  1. NeurIPS 2023On the Adversarial Robustness of Out-of-distribution Generalization Models
  2. NeurIPS 2023On the Robustness of Mechanism Design under Total Variation Distance
  3. NeurIPS 2023On Transfer of Adversarial Robustness from Pretraining to Downstream Tasks
  4. NeurIPS 2023One Less Reason for Filter Pruning: Gaining Free Adversarial Robustness with Structured Grouped Kernel Pruning
  5. NeurIPS 2023Optimal Transport Model Distributional Robustness
  6. NeurIPS 2023PAC-Bayesian Spectrally-Normalized Bounds for Adversarially Robust Generalization
  7. NeurIPS 2023Perturbation Towards Easy Samples Improves Targeted Adversarial Transferability
  8. NeurIPS 2023Provable Adversarial Robustness for Group Equivariant Tasks: Graphs, Point Clouds, Molecules, and More
  9. NeurIPS 2023QuadAttac$K$: A Quadratic Programming Approach to Learning Ordered Top-$K$ Adversarial Attacks
  10. NeurIPS 2023Rethinking the Backward Propagation for Adversarial Transferability
  11. NeurIPS 2023Revisiting Adversarial Robustness Distillation from the Perspective of Robust Fairness
  12. NeurIPS 2023Revisiting Visual Model Robustness: A Frequency Long-Tailed Distribution View
  13. NeurIPS 2023Robust Data Valuation with Weighted Banzhaf Values
  14. NeurIPS 2023Robust Lipschitz Bandits to Adversarial Corruptions
  15. NeurIPS 2023Robust low-rank training via approximate orthonormal constraints
  16. NeurIPS 2023Robust Matrix Sensing in the Semi-Random Model
  17. NeurIPS 2023Robustness Guarantees for Adversarially Trained Neural Networks
  18. NeurIPS 2023RS-Del: Edit Distance Robustness Certificates for Sequence Classifiers via Randomized Deletion
  19. NeurIPS 2023Shared Adversarial Unlearning: Backdoor Mitigation by Unlearning Shared Adversarial Examples
  20. NeurIPS 2023Spatial-frequency channels, shape bias, and adversarial robustness
  21. NeurIPS 2023Spuriosity Rankings: Sorting Data to Measure and Mitigate Biases
  22. NeurIPS 2023Stable Diffusion is Unstable
  23. NeurIPS 2023Static and Sequential Malicious Attacks in the Context of Selective Forgetting
  24. NeurIPS 2023Strong and Precise Modulation of Human Percepts via Robustified ANNs
  25. NeurIPS 2023Temporal Robustness against Data poisoning
  26. NeurIPS 2023The Adversarial Consistency of Surrogate Risks for Binary Classification
  27. NeurIPS 2023The Double-Edged Sword of Implicit Bias: Generalization vs. Robustness in ReLU Networks
  28. NeurIPS 2023Towards Evaluating Transfer-based Attacks Systematically, Practically, and Fairly
  29. NeurIPS 2023Towards Higher Ranks via Adversarial Weight Pruning
  30. NeurIPS 2023Towards Last-layer Retraining for Group Robustness with Fewer Annotations
  31. NeurIPS 2023Training on Foveated Images Improves Robustness to Adversarial Attacks
  32. NeurIPS 2023Transferable Adversarial Robustness for Categorical Data via Universal Robust Embeddings
  33. NeurIPS 2023Transitivity Recovering Decompositions: Interpretable and Robust Fine-Grained Relationships
  34. NeurIPS 2023Understanding and Improving Ensemble Adversarial Defense
  35. NeurIPS 2023UniT: A Unified Look at Certified Robust Training against Text Adversarial Perturbation
  36. NeurIPS 2023Unlocking Deterministic Robustness Certification on ImageNet
  37. NeurIPS 2023VLATTACK: Multimodal Adversarial Attacks on Vision-Language Tasks via Pre-trained Models
  38. NeurIPS 2023Wasserstein distributional robustness of neural networks
  39. NeurIPS 2023What Can We Learn from Unlearnable Datasets?
  40. NeurIPS 2023What Distributions are Robust to Indiscriminate Poisoning Attacks for Linear Learners?

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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.

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