对抗鲁棒论文趋势 2023–2026

主要结论

• 对抗鲁棒论文从 2023 年的 313 篇增长到 2026 年的 317 篇，三年间扩大到约 1.0 倍。
• NeurIPS 是发对抗鲁棒论文最多的会议，2023–2026 年共 422 篇，占四个会议总量的 33%。
• 交叉方向里涨得最快的是对齐与安全：同时属于两个主题的论文从 2023 年的 13 篇增至 2026 年的 56 篇。
• 在「安全与可信」的 5 个主题里，它的 2026 年论文数排第 1；同组增长最快的水印是 9.3 倍，对抗鲁棒是 1.0 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 2026A Little Robustness Is All You Need: Leveraging Predictions for Contextual Optimization
• ICML 2026Bias in Zeroth-Order Normal Estimation for Decision-Based Attacks
• ICLR 2026CERTIFIED VS. EMPIRICAL ADVERSARIAL ROBUSTNESS VIA HYBRID CONVOLUTIONS WITH ATTENTION STOCHASTICITY
• CVPR 2026A Combination of Noise and Bilateral Filters Achieve Supralinear and
• NeurIPS 2025A Unified Approach to Submodular Maximization Under Noise
• ICML 2025Adversarial Perturbations Are Formed by Iteratively Learning Linear Combinations of the Right Singular Vectors of the Adversarial Jacobian
• ICLR 2025$\sigma$-zero: Gradient-based Optimization of $\ell_0$-norm Adversarial Examples
• CVPR 2025A Unified, Resilient, and Explainable Adversarial Patch Detector
• NeurIPS 2024A StrongREJECT for Empty Jailbreaks
• ICML 2024Adversarial Attacks on Combinatorial Multi-Armed Bandits
• ICLR 2024An LLM can Fool Itself: A Prompt-Based Adversarial Attack
• CVPR 2024Defense Against Adversarial Attacks on No-Reference Image Quality Models with Gradient Norm Regularization
• NeurIPS 2023A Closer Look at the Robustness of Contrastive Language-Image Pre-Training (CLIP)
• ICML 2023A Law of Robustness beyond Isoperimetry
• ICLR 2023A law of adversarial risk, interpolation, and label noise
• CVPR 2023Adversarial Normalization: I Can Visualize Everything (ICE)
• NeurIPS 2026A Regularization-Based Approach to Public Belief State Search for Adversarial Games
• ICML 2026CaliDist: Calibrating Large Language Models via Behavioral Robustness to Distraction
• ICLR 2026Conformal Robustness Control: A New Strategy for Robust Decision
• CVPR 2026A Provable Energy-Guided Test-Time Defense Boosting Adversarial Robustness of Large

全部对抗鲁棒论文

共 73 篇，第 2 / 2 页

51. ICML 2024RAUCA: A Novel Physical Adversarial Attack on Vehicle Detectors via Robust and Accurate Camouflage Generation
52. ICML 2024Rethinking Adversarial Robustness in the Context of the Right to be Forgotten
53. ICML 2024Revealing the Dark Secrets of Extremely Large Kernel ConvNets on Robustness
54. ICML 2024Revisiting Character-level Adversarial Attacks for Language Models
55. ICML 2024Riemannian Accelerated Zeroth-order Algorithm: Improved Robustness and Lower Query Complexity
56. ICML 2024Robust CLIP: Unsupervised Adversarial Fine-Tuning of Vision Embeddings for Robust Large Vision-Language Models
57. ICML 2024Robust Stable Spiking Neural Networks
58. ICML 2024Robust Universal Adversarial Perturbations
59. ICML 2024Robustness of Deep Learning for Accelerated MRI: Benefits of Diverse Training Data
60. ICML 2024Robustness of Nonlinear Representation Learning
61. ICML 2024Roping in Uncertainty: Robustness and Regularization in Markov Games
62. ICML 2024SignSGD with Federated Defense: Harnessing Adversarial Attacks through Gradient Sign Decoding
63. ICML 2024The Perception-Robustness Tradeoff in Deterministic Image Restoration
64. ICML 2024The Pitfalls and Promise of Conformal Inference Under Adversarial Attacks
65. ICML 2024Towards Efficient Training and Evaluation of Robust Models against $l_0$ Bounded Adversarial Perturbations
66. ICML 2024Towards Optimal Adversarial Robust Q-learning with Bellman Infinity-error
67. ICML 2024Towards Robust Model-Based Reinforcement Learning Against Adversarial Corruption
68. ICML 2024Triadic-OCD: Asynchronous Online Change Detection with Provable Robustness, Optimality, and Convergence
69. ICML 2024Two Heads are Actually Better than One: Towards Better Adversarial Robustness via Transduction and Rejection
70. ICML 2024Two Tales of Single-Phase Contrastive Hebbian Learning
71. ICML 2024Uniformly Stable Algorithms for Adversarial Training and Beyond
72. ICML 2024VNN: Verification-Friendly Neural Networks with Hard Robustness Guarantees
73. ICML 2024WAVES: Benchmarking the Robustness of Image Watermarks

常见问题

2023–2026 年四大会议一共有多少篇对抗鲁棒论文？

共 1,291 篇，按年份分别是 2023 年 313 篇、2024 年 334 篇、2025 年 327 篇、2026 年 317 篇。

NeurIPS 2026 有多少篇对抗鲁棒论文？

NeurIPS 2026 有 81 篇对抗鲁棒论文，上一届是 110 篇。

ICLR 2026 有多少篇对抗鲁棒论文？

ICLR 2026 有 94 篇对抗鲁棒论文，上一届是 88 篇。

ICML 2026 有多少篇对抗鲁棒论文？

ICML 2026 有 93 篇对抗鲁棒论文，上一届是 85 篇。

CVPR 2026 有多少篇对抗鲁棒论文？

CVPR 2026 有 49 篇对抗鲁棒论文，上一届是 44 篇。

哪个会议的对抗鲁棒论文最多？

NeurIPS，2023–2026 年共 422 篇。