对抗鲁棒论文趋势 2023–2026
对抗样本与防御
统计范围：NeurIPS、ICLR、ICML、CVPR 四个会议，2023–2026 年，共 1,291 篇被归入该主题的论文。
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。
各会议论文数
按年份和会议统计
| 年份 | NeurIPS | ICLR | ICML | CVPR | 合计 |
|---|---|---|---|---|---|
| 2023 | 100 | 79 | 60 | 74 | 313 |
| 2024 | 131 | 70 | 73 | 60 | 334 |
| 2025 | 110 | 88 | 85 | 44 | 327 |
| 2026 | 81 | 94 | 93 | 49 | 317 |
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 110 篇，第 3 / 3 页
- NeurIPS 2025The Right to Red-Team: Adversarial AI Literacy as a Civic Imperative in K-12 Education
- NeurIPS 2025The Unseen Threat: Residual Knowledge in Machine Unlearning under Perturbed Samples
- NeurIPS 2025Theoretical Guarantees for the Retention of Strict Nash Equilibria by Coevolutionary Algorithms
- NeurIPS 2025Transstratal Adversarial Attack: Compromising Multi-Layered Defenses in Text-to-Image Models
- NeurIPS 2025Understanding and Improving Adversarial Robustness of Neural Probabilistic Circuits
- NeurIPS 2025Understanding and Improving Fast Adversarial Training against $l_0$ Bounded Perturbations
- NeurIPS 2025Vanish into Thin Air: Cross-prompt Universal Adversarial Attacks for SAM2
- NeurIPS 2025Vulnerable Data-Aware Adversarial Training
- NeurIPS 2025When Are Concepts Erased From Diffusion Models?
- NeurIPS 2025When Does Closeness in Distribution Imply Representational Similarity? An Identifiability Perspective
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 查对抗鲁棒在 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": "adversarial-robustness"}
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。