Robustness Benchmarks papers, 2023–2026

Key findings

• Robustness Benchmarks went from 64 papers in 2023 to 69 in 2026, roughly 1.1x in three years.
• NeurIPS publishes the most Robustness Benchmarks work: 80 papers from 2023 to 2026, 30% of the four-venue total.
• The fastest-growing overlap is with General ML · evaluation: papers tagged with both rose from 0 in 2023 to 8 in 2026.
• Among the 5 topics under Evaluation and Benchmarks, it ranks #4 by 2026 paper count; the fastest grower in the group, LLM Benchmarks, is up 154x versus 1.1x here.

Representative papers

Spread across years and venues so every edition shows up

• NeurIPS 2026Brittlebench: Quantifying LLM robustness via prompt sensitivity
• ICML 2026Geometrically Constrained Outlier Synthesis
• ICLR 2026Pitfalls in Evaluating Language Model Forecasters
• CVPR 2026FoV-Net Rotation-Invariant CAD B-rep Learning via Field-of-View Ray Casting
• NeurIPS 2025Aggregation Hides Out-of-Distribution Generalization Failures from Spurious Correlations
• ICML 2025Diverse Prototypical Ensembles Improve Robustness to Subpopulation Shift
• ICLR 2025DRoP: Distributionally Robust Data Pruning
• CVPR 2025FRAMES-VQA: Benchmarking Fine-Tuning Robustness across Multi-Modal Shifts in Visual Question Answering
• NeurIPS 2024An Analysis of Robustness of Non-Lipschitz Networks
• ICML 2024Controllable Prompt Tuning For Balancing Group Distributional Robustness
• ICLR 2024Realistic Evaluation of Semi-supervised Learning Algorithms in Open Environments
• CVPR 2024A Bayesian Approach to OOD Robustness in Image Classification
• NeurIPS 2023Revisiting Out-of-distribution Robustness in NLP: Benchmarks, Analysis, and LLMs Evaluations
• ICML 2023A Law of Robustness beyond Isoperimetry
• ICLR 2023A Call to Reflect on Evaluation Practices for Failure Detection in Image Classification
• CVPR 2023Improving Robustness of Vision Transformers by Reducing Sensitivity To Patch Corruptions
• NeurIPS 2026Stress-Testing Neural Network Verifiers with Provably Robust Instances
• ICML 2026Optimal Attention Temperature Improves the Robustness of In-Context Learning under Distribution Shift in High Dimensions
• ICLR 2026CLARC: C/C++ Benchmark for Robust Code Search
• CVPR 2026LIBERO-Plus A Progressive Robustness Benchmark for Visual-Language-Action Models

All Robustness Benchmarks papers

64 papers, page 1 of 2

1. CVPR 2023A Large-Scale Robustness Analysis of Video Action Recognition Models
2. CVPR 2023Adversarial Robustness via Random Projection Filters
3. CVPR 2023Benchmarking Robustness of 3D Object Detection to Common Corruptions
4. CVPR 2023Cooperation or Competition: Avoiding Player Domination for Multi-Target Robustness via Adaptive Budgets
5. CVPR 2023Detecting Backdoors During the Inference Stage Based on Corruption Robustness Consistency
6. CVPR 2023ImageNet-E: Benchmarking Neural Network Robustness via Attribute Editing
7. CVPR 2023Improving Robustness of Vision Transformers by Reducing Sensitivity To Patch Corruptions
8. CVPR 2023Revisiting Residual Networks for Adversarial Robustness
9. CVPR 2023Towards Compositional Adversarial Robustness: Generalizing Adversarial Training to Composite Semantic Perturbations
10. ICLR 2023A Call to Reflect on Evaluation Practices for Failure Detection in Image Classification
11. ICLR 2023A Unified Algebraic Perspective on Lipschitz Neural Networks
12. ICLR 2023Bitrate-Constrained DRO: Beyond Worst Case Robustness To Unknown Group Shifts
13. ICLR 2023Can CNNs Be More Robust Than Transformers?
14. ICLR 2023Certified Training: Small Boxes are All You Need
15. ICLR 2023Data augmentation alone can improve adversarial training
16. ICLR 2023Distributionally Robust Post-hoc Classifiers under Prior Shifts
17. ICLR 2023Diversify and Disambiguate: Out-of-Distribution Robustness via Disagreement
18. ICLR 2023Dr.Spider: A Diagnostic Evaluation Benchmark towards Text-to-SQL Robustness
19. ICLR 2023Feature Reconstruction From Outputs Can Mitigate Simplicity Bias in Neural Networks
20. ICLR 2023Holistic Adversarially Robust Pruning
21. ICLR 2023Last Layer Re-Training is Sufficient for Robustness to Spurious Correlations
22. ICLR 2023Localized Randomized Smoothing for Collective Robustness Certification
23. ICLR 2023Multi-lingual Evaluation of Code Generation Models
24. ICLR 2023On Explaining Neural Network Robustness with Activation Path
25. ICLR 2023On the Perils of Cascading Robust Classifiers
26. ICLR 2023Probabilistically Robust Recourse: Navigating the Trade-offs between Costs and Robustness in Algorithmic Recourse
27. ICLR 2023Prompting GPT-3 To Be Reliable
28. ICLR 2023Provable Defense Against Geometric Transformations
29. ICLR 2023Provable Robustness against Wasserstein Distribution Shifts via Input Randomization
30. ICLR 2023Pushing the Accuracy-Group Robustness Frontier with Introspective Self-play
31. ICLR 2023Revisiting adapters with adversarial training
32. ICLR 2023Robustness to corruption in pre-trained Bayesian neural networks
33. ICLR 2023Sound Randomized Smoothing in Floating-Point Arithmetic
34. ICLR 2023Squeeze Training for Adversarial Robustness
35. ICLR 2023TextGrad: Advancing Robustness Evaluation in NLP by Gradient-Driven Optimization
36. ICLR 2023The Asymmetric Maximum Margin Bias of Quasi-Homogeneous Neural Networks
37. ICLR 2023The Lazy Neuron Phenomenon: On Emergence of Activation Sparsity in Transformers
38. ICLR 2023Towards Robustness Certification Against Universal Perturbations
39. ICML 2023A Law of Robustness beyond Isoperimetry
40. ICML 2023Adversarial robustness of amortized Bayesian inference
41. ICML 2023BNN-DP: Robustness Certification of Bayesian Neural Networks via Dynamic Programming
42. ICML 2023Do Perceptually Aligned Gradients Imply Robustness?
43. ICML 2023Extending Kernel PCA through Dualization: Sparsity, Robustness and Fast Algorithms
44. ICML 2023GraphCleaner: Detecting Mislabelled Samples in Popular Graph Learning Benchmarks
45. ICML 2023How Many Perturbations Break This Model? Evaluating Robustness Beyond Adversarial Accuracy
46. ICML 2023Improving Adversarial Robustness by Putting More Regularizations on Less Robust Samples
47. ICML 2023Improving Adversarial Robustness of Deep Equilibrium Models with Explicit Regulations Along the Neural Dynamics
48. ICML 2023Improving l1-Certified Robustness via Randomized Smoothing by Leveraging Box Constraints
49. ICML 2023Robust Weight Signatures: Gaining Robustness as Easy as Patching Weights?
50. ICML 2023Robustness in Multimodal Learning under Train-Test Modality Mismatch

FAQ

How many Robustness Benchmarks papers were published at NeurIPS, ICLR, ICML and CVPR from 2023 to 2026?

264 in total: 64 in 2023, 59 in 2024, 72 in 2025, 69 in 2026.

How many Robustness Benchmarks papers are at NeurIPS 2026?

NeurIPS 2026 has 18 Robustness Benchmarks papers, versus 34 the year before.

How many Robustness Benchmarks papers are at ICLR 2026?

ICLR 2026 has 15 Robustness Benchmarks papers, versus 10 the year before.

How many Robustness Benchmarks papers are at ICML 2026?

ICML 2026 has 24 Robustness Benchmarks papers, versus 20 the year before.

How many Robustness Benchmarks papers are at CVPR 2026?

CVPR 2026 has 12 Robustness Benchmarks papers, versus 8 the year before.

Which conference publishes the most Robustness Benchmarks papers?

NeurIPS, with 80 papers from 2023 to 2026.