鲁棒基准论文趋势 2023–2026

主要结论

• 鲁棒基准论文从 2023 年的 64 篇增长到 2026 年的 69 篇，三年间扩大到约 1.1 倍。
• NeurIPS 是发鲁棒基准论文最多的会议，2023–2026 年共 80 篇，占四个会议总量的 30%。
• 交叉方向里涨得最快的是通用机器学习 · evaluation：同时属于两个主题的论文从 2023 年的 0 篇增至 2026 年的 8 篇。
• 在「评测与基准」的 5 个主题里，它的 2026 年论文数排第 4；同组增长最快的大模型基准是 154 倍，鲁棒基准是 1.1 倍。

代表论文

按年份和会议均匀挑选，方便快速看到每一届的样貌

• 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

全部鲁棒基准论文

共 59 篇，第 1 / 2 页

1. CVPR 2024A Bayesian Approach to OOD Robustness in Image Classification
2. CVPR 2024Benchmarking the Robustness of Temporal Action Detection Models Against Temporal Corruptions
3. CVPR 2024Bilateral Adaptation for Human-Object Interaction Detection with Occlusion-Robustness
4. CVPR 2024Calibrating Multi-modal Representations: A Pursuit of Group Robustness without Annotations
5. CVPR 2024ImageNet-D: Benchmarking Neural Network Robustness on Diffusion Synthetic Object
6. CVPR 2024Model Inversion Robustness: Can Transfer Learning Help?
7. CVPR 2024Reconstructing Hands in 3D with Transformers
8. CVPR 2024RoDLA: Benchmarking the Robustness of Document Layout Analysis Models
9. CVPR 2024Soften to Defend: Towards Adversarial Robustness via Self-Guided Label Refinement
10. ICLR 2024A Benchmark Study on Calibration
11. ICLR 2024A Recipe for Improved Certifiable Robustness
12. ICLR 2024Annealing Self-Distillation Rectification Improves Adversarial Training
13. ICLR 2024Boosting the Adversarial Robustness of Graph Neural Networks: An OOD Perspective
14. ICLR 2024Does CLIP’s generalization performance mainly stem from high train-test similarity?
15. ICLR 2024DRSM: De-Randomized Smoothing on Malware Classifier Providing Certified Robustness
16. ICLR 2024Evaluating Large Language Models at Evaluating Instruction Following
17. ICLR 2024Evaluating the Zero-shot Robustness of Instruction-tuned Language Models
18. ICLR 2024Expressive Losses for Verified Robustness via Convex Combinations
19. ICLR 2024Foundation Model-oriented Robustness: Robust Image Model Evaluation with Pretrained Models
20. ICLR 2024ImageNet-OOD: Deciphering Modern Out-of-Distribution Detection Algorithms
21. ICLR 2024Large Language Models Are Not Robust Multiple Choice Selectors
22. ICLR 2024MetaPhysiCa: Improving OOD Robustness in Physics-informed Machine Learning
23. ICLR 2024Mitigating the Curse of Dimensionality for Certified Robustness via Dual Randomized Smoothing
24. ICLR 2024Quantifying Language Models' Sensitivity to Spurious Features in Prompt Design or: How I learned to start worrying about prompt formatting
25. ICLR 2024Realistic Evaluation of Semi-supervised Learning Algorithms in Open Environments
26. ICLR 2024Towards Robust Out-of-Distribution Generalization Bounds via Sharpness
27. ICLR 2024Understanding Domain Generalization: A Noise Robustness Perspective
28. ICML 2024Can Implicit Bias Imply Adversarial Robustness?
29. ICML 2024Connect Later: Improving Fine-tuning for Robustness with Targeted Augmentations
30. ICML 2024Controllable Prompt Tuning For Balancing Group Distributional Robustness
31. ICML 2024Density Ratio Estimation with Doubly Strong Robustness
32. ICML 2024Enhancing Adversarial Robustness in SNNs with Sparse Gradients
33. ICML 2024Et Tu Certifications: Robustness Certificates Yield Better Adversarial Examples
34. ICML 2024Improving Accuracy-robustness Trade-off via Pixel Reweighted Adversarial Training
35. ICML 2024Improving Group Robustness on Spurious Correlation Requires Preciser Group Inference
36. ICML 2024Multigroup Robustness
37. ICML 2024OODRobustBench: a Benchmark and Large-Scale Analysis of Adversarial Robustness under Distribution Shift
38. ICML 2024Position: Exploring the Robustness of Pipeline-Parallelism-Based Decentralized Training
39. ICML 2024Revealing the Dark Secrets of Extremely Large Kernel ConvNets on Robustness
40. ICML 2024Robustness of Deep Learning for Accelerated MRI: Benefits of Diverse Training Data
41. ICML 2024Robustness of Nonlinear Representation Learning
42. ICML 2024WAVES: Benchmarking the Robustness of Image Watermarks
43. ICML 2024What Would Gauss Say About Representations? Probing Pretrained Image Models using Synthetic Gaussian Benchmarks
44. NeurIPS 2024A Sober Look at the Robustness of CLIPs to Spurious Features
45. NeurIPS 2024A StrongREJECT for Empty Jailbreaks
46. NeurIPS 2024Adaptive Randomized Smoothing: Certified Adversarial Robustness for Multi-Step Defences
47. NeurIPS 2024An Analysis of Robustness of Non-Lipschitz Networks
48. NeurIPS 2024BetterBench: Assessing AI Benchmarks, Uncovering Issues, and Establishing Best Practices
49. NeurIPS 2024FedLLM-Bench: Realistic Benchmarks for Federated Learning of Large Language Models
50. NeurIPS 2024GREAT Score: Global Robustness Evaluation of Adversarial Perturbation using Generative Models

常见问题

2023–2026 年四大会议一共有多少篇鲁棒基准论文？

共 264 篇，按年份分别是 2023 年 64 篇、2024 年 59 篇、2025 年 72 篇、2026 年 69 篇。

NeurIPS 2026 有多少篇鲁棒基准论文？

NeurIPS 2026 有 18 篇鲁棒基准论文，上一届是 34 篇。

ICLR 2026 有多少篇鲁棒基准论文？

ICLR 2026 有 15 篇鲁棒基准论文，上一届是 10 篇。

ICML 2026 有多少篇鲁棒基准论文？

ICML 2026 有 24 篇鲁棒基准论文，上一届是 20 篇。

CVPR 2026 有多少篇鲁棒基准论文？

CVPR 2026 有 12 篇鲁棒基准论文，上一届是 8 篇。

哪个会议的鲁棒基准论文最多？

NeurIPS，2023–2026 年共 80 篇。