Robustness Benchmarks papers, 2023–2026
OOD evaluation
Scope: NeurIPS, ICLR, ICML and CVPR, 2023–2026. 264 papers are tagged with this topic.
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.
Papers per venue
Counts by year and venue
| Year | NeurIPS | ICLR | ICML | CVPR | Total |
|---|---|---|---|---|---|
| 2023 | 12 | 29 | 14 | 9 | 64 |
| 2024 | 16 | 18 | 16 | 9 | 59 |
| 2025 | 34 | 10 | 20 | 8 | 72 |
| 2026 | 18 | 15 | 24 | 12 | 69 |
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
72 papers, page 1 of 2
- ICLR 2026CERTIFIED VS. EMPIRICAL ADVERSARIAL ROBUSTNESS VIA HYBRID CONVOLUTIONS WITH ATTENTION STOCHASTICITY
- ICLR 2026CLARC: C/C++ Benchmark for Robust Code Search
- ICLR 2026GneissWeb: Preparing High Quality Data for LLMs at Scale
- ICLR 2026GraphUniverse: Enabling Systematic Evaluation of Inductive Generalization
- ICLR 2026Is Your Paper Being Reviewed by an LLM? Benchmarking AI Text Detection in Peer Review
- ICLR 2026Mapping Overlaps in Benchmarks through Perplexity in the Wild
- ICLR 2026On the Bayes Inconsistency of Disagreement Discrepancy Surrogates
- ICLR 2026ON THE ROLE OF IMPLICIT REGULARIZATION OF STOCHASTIC GRADIENT DESCENT IN GROUP ROBUSTNESS
- ICLR 2026Pitfalls in Evaluating Language Model Forecasters
- ICLR 2026PYRREGULAR: A Unified Framework for Irregular Time Series, with Classification Benchmarks
- ICLR 2026QUEST: A robust attention formulation using query-modulated spherical attention
- ICLR 2026SocialHarmBench: Revealing LLM Vulnerabilities to Socially Harmful Requests
- ICLR 2026The Price of Robustness: Stable Classifiers Need Overparameterization
- ICLR 2026Training Dynamics Impact Post-Training Quantization Robustness
- ICLR 2026When Flatness Does (Not) Guarantee Adversarial Robustness
- ICLR 2025Adversarially Robust Out-of-Distribution Detection Using Lyapunov-Stabilized Embeddings
- ICLR 2025Adversaries With Incentives: A Strategic Alternative to Adversarial Robustness
- ICLR 2025Consistency Checks for Language Model Forecasters
- ICLR 2025Directional Gradient Projection for Robust Fine-Tuning of Foundation Models
- ICLR 2025Do Large Language Models Truly Understand Geometric Structures?
- ICLR 2025DRoP: Distributionally Robust Data Pruning
- ICLR 2025In Search of Forgotten Domain Generalization
- ICLR 2025MixMax: Distributional Robustness in Function Space via Optimal Data Mixtures
- ICLR 2025THE ROBUSTNESS OF DIFFERENTIABLE CAUSAL DISCOVERY IN MISSPECIFIED SCENARIOS
- ICLR 2025Zero-cost Proxy for Adversarial Robustness Evaluation
- ICLR 2024A Benchmark Study on Calibration
- ICLR 2024A Recipe for Improved Certifiable Robustness
- ICLR 2024Annealing Self-Distillation Rectification Improves Adversarial Training
- ICLR 2024Boosting the Adversarial Robustness of Graph Neural Networks: An OOD Perspective
- ICLR 2024Does CLIP’s generalization performance mainly stem from high train-test similarity?
- ICLR 2024DRSM: De-Randomized Smoothing on Malware Classifier Providing Certified Robustness
- ICLR 2024Evaluating Large Language Models at Evaluating Instruction Following
- ICLR 2024Evaluating the Zero-shot Robustness of Instruction-tuned Language Models
- ICLR 2024Expressive Losses for Verified Robustness via Convex Combinations
- ICLR 2024Foundation Model-oriented Robustness: Robust Image Model Evaluation with Pretrained Models
- ICLR 2024ImageNet-OOD: Deciphering Modern Out-of-Distribution Detection Algorithms
- ICLR 2024Large Language Models Are Not Robust Multiple Choice Selectors
- ICLR 2024MetaPhysiCa: Improving OOD Robustness in Physics-informed Machine Learning
- ICLR 2024Mitigating the Curse of Dimensionality for Certified Robustness via Dual Randomized Smoothing
- ICLR 2024Quantifying Language Models' Sensitivity to Spurious Features in Prompt Design or: How I learned to start worrying about prompt formatting
- ICLR 2024Realistic Evaluation of Semi-supervised Learning Algorithms in Open Environments
- ICLR 2024Towards Robust Out-of-Distribution Generalization Bounds via Sharpness
- ICLR 2024Understanding Domain Generalization: A Noise Robustness Perspective
- ICLR 2023A Call to Reflect on Evaluation Practices for Failure Detection in Image Classification
- ICLR 2023A Unified Algebraic Perspective on Lipschitz Neural Networks
- ICLR 2023Bitrate-Constrained DRO: Beyond Worst Case Robustness To Unknown Group Shifts
- ICLR 2023Can CNNs Be More Robust Than Transformers?
- ICLR 2023Certified Training: Small Boxes are All You Need
- ICLR 2023Data augmentation alone can improve adversarial training
- ICLR 2023Distributionally Robust Post-hoc Classifiers under Prior Shifts
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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.