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 334 篇，第 7 / 7 页

301. NeurIPS 2024REDUCR: Robust Data Downsampling using Class Priority Reweighting
302. NeurIPS 2024Relational Verification Leaps Forward with RABBit
303. NeurIPS 2024Reproducibility Study on Adversarial Attacks Against Robust Transformer Trackers
304. NeurIPS 2024Rethinking LLM Memorization through the Lens of Adversarial Compression
305. NeurIPS 2024ROBIN: Robust and Invisible Watermarks for Diffusion Models with Adversarial Optimization
306. NeurIPS 2024Robust Graph Neural Networks via Unbiased Aggregation
307. NeurIPS 2024Robust Neural Contextual Bandit against Adversarial Corruptions
308. NeurIPS 2024Sample and Computationally Efficient Robust Learning of Gaussian Single-Index Models
309. NeurIPS 2024Self-Supervised Adversarial Training via Diverse Augmented Queries and Self-Supervised Double Perturbation
310. NeurIPS 2024SETBENCH: Assessing the Analytical and Semantic Robustness of Language Models
311. NeurIPS 2024SETLEXSEM CHALLENGE: Using Set Operations to Evaluate the Lexical and Semantic Robustness of Language Models
312. NeurIPS 2024Soft Prompt Threats: Attacking Safety Alignment and Unlearning in Open-Source LLMs through the Embedding Space
313. NeurIPS 2024Stability and Generalization of Adversarial Training for Shallow Neural Networks with Smooth Activation
314. NeurIPS 2024Stress-Testing Long-Context Language Models with Lifelong ICL and Task Haystack
315. NeurIPS 2024SuperDeepFool: a new fast and accurate minimal adversarial attack
316. NeurIPS 2024TabularBench: Benchmarking Adversarial Robustness for Tabular Deep Learning in Real-world Use-cases
317. NeurIPS 2024Taming Heavy-Tailed Losses in Adversarial Bandits and the Best-of-Both-Worlds Setting
318. NeurIPS 2024Target-Guided Adversarial Point Cloud Transformer Towards Recognition Against Real-world Corruptions
319. NeurIPS 2024TARP-VP: Towards Evaluation of Transferred Adversarial Robustness and Privacy on Label Mapping Visual Prompting Models
320. NeurIPS 2024Text-Guided Attention is All You Need for Zero-Shot Robustness in Vision-Language Models
321. NeurIPS 2024The Group Robustness is in the Details: Revisiting Finetuning under Spurious Correlations
322. NeurIPS 2024The Implicit Bias of Gradient Descent toward Collaboration between Layers: A Dynamic Analysis of Multilayer Perceptions
323. NeurIPS 2024The Price of Implicit Bias in Adversarially Robust Generalization
324. NeurIPS 2024The Secretary Problem with Predicted Additive Gap
325. NeurIPS 2024Transferability Bound Theory: Exploring Relationship between Adversarial Transferability and Flatness
326. NeurIPS 2024Transferable Adversarial Attacks on SAM and Its Downstream Models
327. NeurIPS 2024Treatment of Statistical Estimation Problems in Randomized Smoothing for Adversarial Robustness
328. NeurIPS 2024Uncertainty-based Offline Variational Bayesian Reinforcement Learning for Robustness under Diverse Data Corruptions
329. NeurIPS 2024Understanding and Improving Adversarial Collaborative Filtering for Robust Recommendation
330. NeurIPS 2024United We Stand, Divided We Fall: Fingerprinting Deep Neural Networks via Adversarial Trajectories
331. NeurIPS 2024Unveiling the Potential of Robustness in Selecting Conditional Average Treatment Effect Estimators
332. NeurIPS 2024WaterMax: breaking the LLM watermark detectability-robustness-quality trade-off
333. NeurIPS 2024Weight for Robustness: A Comprehensive Approach towards Optimal Fault-Tolerant Asynchronous ML
334. NeurIPS 2024Wide Two-Layer Networks can Learn from Adversarial Perturbations

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。