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 72 篇，第 1 / 2 页

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

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。