鲁棒基准论文趋势 2023–2026

分布外评测

统计范围：NeurIPS、ICLR、ICML、CVPR 四个会议，2023–2026 年，共 264 篇被归入该主题的论文。

主要结论

每年论文数

各会议论文数

按年份和会议统计

鲁棒基准论文数，按年份和会议
年份NeurIPSICLRICMLCVPR合计
2023122914964
2024161816959
2025341020872
20261815241269

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

全部鲁棒基准论文

年份全部2023202420252026
会议全部NeurIPSICLRICMLCVPR

共 264 篇，第 4 / 6 页

  1. ICLR 2024A Benchmark Study on Calibration
  2. ICLR 2024A Recipe for Improved Certifiable Robustness
  3. ICLR 2024Annealing Self-Distillation Rectification Improves Adversarial Training
  4. ICLR 2024Boosting the Adversarial Robustness of Graph Neural Networks: An OOD Perspective
  5. ICLR 2024Does CLIP’s generalization performance mainly stem from high train-test similarity?
  6. ICLR 2024DRSM: De-Randomized Smoothing on Malware Classifier Providing Certified Robustness
  7. ICLR 2024Evaluating Large Language Models at Evaluating Instruction Following
  8. ICLR 2024Evaluating the Zero-shot Robustness of Instruction-tuned Language Models
  9. ICLR 2024Expressive Losses for Verified Robustness via Convex Combinations
  10. ICLR 2024Foundation Model-oriented Robustness: Robust Image Model Evaluation with Pretrained Models
  11. ICLR 2024ImageNet-OOD: Deciphering Modern Out-of-Distribution Detection Algorithms
  12. ICLR 2024Large Language Models Are Not Robust Multiple Choice Selectors
  13. ICLR 2024MetaPhysiCa: Improving OOD Robustness in Physics-informed Machine Learning
  14. ICLR 2024Mitigating the Curse of Dimensionality for Certified Robustness via Dual Randomized Smoothing
  15. ICLR 2024Quantifying Language Models' Sensitivity to Spurious Features in Prompt Design or: How I learned to start worrying about prompt formatting
  16. ICLR 2024Realistic Evaluation of Semi-supervised Learning Algorithms in Open Environments
  17. ICLR 2024Towards Robust Out-of-Distribution Generalization Bounds via Sharpness
  18. ICLR 2024Understanding Domain Generalization: A Noise Robustness Perspective
  19. ICML 2024Can Implicit Bias Imply Adversarial Robustness?
  20. ICML 2024Connect Later: Improving Fine-tuning for Robustness with Targeted Augmentations
  21. ICML 2024Controllable Prompt Tuning For Balancing Group Distributional Robustness
  22. ICML 2024Density Ratio Estimation with Doubly Strong Robustness
  23. ICML 2024Enhancing Adversarial Robustness in SNNs with Sparse Gradients
  24. ICML 2024Et Tu Certifications: Robustness Certificates Yield Better Adversarial Examples
  25. ICML 2024Improving Accuracy-robustness Trade-off via Pixel Reweighted Adversarial Training
  26. ICML 2024Improving Group Robustness on Spurious Correlation Requires Preciser Group Inference
  27. ICML 2024Multigroup Robustness
  28. ICML 2024OODRobustBench: a Benchmark and Large-Scale Analysis of Adversarial Robustness under Distribution Shift
  29. ICML 2024Position: Exploring the Robustness of Pipeline-Parallelism-Based Decentralized Training
  30. ICML 2024Revealing the Dark Secrets of Extremely Large Kernel ConvNets on Robustness
  31. ICML 2024Robustness of Deep Learning for Accelerated MRI: Benefits of Diverse Training Data
  32. ICML 2024Robustness of Nonlinear Representation Learning
  33. ICML 2024WAVES: Benchmarking the Robustness of Image Watermarks
  34. ICML 2024What Would Gauss Say About Representations? Probing Pretrained Image Models using Synthetic Gaussian Benchmarks
  35. NeurIPS 2024A Sober Look at the Robustness of CLIPs to Spurious Features
  36. NeurIPS 2024A StrongREJECT for Empty Jailbreaks
  37. NeurIPS 2024Adaptive Randomized Smoothing: Certified Adversarial Robustness for Multi-Step Defences
  38. NeurIPS 2024An Analysis of Robustness of Non-Lipschitz Networks
  39. NeurIPS 2024BetterBench: Assessing AI Benchmarks, Uncovering Issues, and Establishing Best Practices
  40. NeurIPS 2024FedLLM-Bench: Realistic Benchmarks for Federated Learning of Large Language Models
  41. NeurIPS 2024GREAT Score: Global Robustness Evaluation of Adversarial Perturbation using Generative Models
  42. NeurIPS 2024Improving robustness to corruptions with multiplicative weight perturbations
  43. NeurIPS 2024Intrinsic Robustness of Prophet Inequality to Strategic Reward Signaling
  44. NeurIPS 2024JailbreakBench: An Open Robustness Benchmark for Jailbreaking Large Language Models
  45. NeurIPS 2024Mitigating Spurious Correlations via Disagreement Probability
  46. NeurIPS 2024On the Worst Prompt Performance of Large Language Models
  47. NeurIPS 2024Predicting the Performance of Foundation Models via Agreement-on-the-Line
  48. NeurIPS 2024Provable Editing of Deep Neural Networks using Parametric Linear Relaxation
  49. NeurIPS 2024TabularBench: Benchmarking Adversarial Robustness for Tabular Deep Learning in Real-world Use-cases
  50. NeurIPS 2024The Group Robustness is in the Details: Revisiting Finetuning under Spurious Correlations

在 Claude、Cursor 里直接问这个趋势

接上 Paperlist MCP 后，写综述、挑方向或准备投稿时，不用离开对话框就能拿到这页的数字：每年各会议的论文数、增长倍数、涨得最快的子方向和代表论文，AI 会按你的问题整理。

可以直接复制这句话问 AI

用 paperlist 查鲁棒基准在 NeurIPS 2023–2026 的论文趋势，哪一年涨得最快？

AI 会调用的工具：get_topic_stats {"topic": "robustness-benchmarks"}

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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。

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