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 327 篇，第 6 / 7 页

251. NeurIPS 2025DepthVanish: Optimizing Adversarial Interval Structures for Stereo-Depth-Invisible Patches
252. NeurIPS 2025DiffBreak: Is Diffusion-Based Purification Robust?
253. NeurIPS 2025Diffusion Guided Adversarial State Perturbations in Reinforcement Learning
254. NeurIPS 2025Distributional Adversarial Attacks and Training in Deep Hedging
255. NeurIPS 2025Ditch the Denoiser: Emergence of Noise Robustness in Self-Supervised Learning from Data Curriculum
256. NeurIPS 2025Dynamic Siamese Expansion Framework for Improving Robustness in Online Continual Learning
257. NeurIPS 2025Dynamical Low-Rank Compression of Neural Networks with Robustness under Adversarial Attacks
258. NeurIPS 2025E2E-VGuard: Adversarial Prevention for Production LLM-based End-To-End Speech Synthesis
259. NeurIPS 2025Enhancing CLIP Robustness via Cross-Modality Alignment
260. NeurIPS 2025Enhancing Graph Classification Robustness with Singular Pooling
261. NeurIPS 2025Enhancing Visual Prompting through Expanded Transformation Space and Overfitting Mitigation
262. NeurIPS 2025Evaluating and Learning Optimal Dynamic Treatment Regimes under Truncation by Death
263. NeurIPS 2025Exploring Semantic-constrained Adversarial Example with Instruction Uncertainty Reduction
264. NeurIPS 2025Exploring the Noise Robustness of Online Conformal Prediction
265. NeurIPS 2025Fair Representation Learning with Controllable High Confidence Guarantees via Adversarial Inference
266. NeurIPS 2025Fit the Distribution: Cross-Image/Prompt Adversarial Attacks on Multimodal Large Language Models
267. NeurIPS 2025Fortifying Time Series: DTW-Certified Robust Anomaly Detection
268. NeurIPS 2025FrameShield: Adversarially Robust Video Anomaly Detection
269. NeurIPS 2025Generative Data Augmentation via Diffusion Distillation, Adversarial Alignment, and Importance Reweighting
270. NeurIPS 2025Harnessing the Computation Redundancy in ViTs to Boost Adversarial Transferability
271. NeurIPS 2025Heterogeneous Adversarial Play in Interactive Environments
272. NeurIPS 2025HQA-VLAttack: Towards High Quality Adversarial Attack on Vision-Language Pre-Trained Models
273. NeurIPS 2025IMPACT: Irregular Multi-Patch Adversarial Composition Based on Two‑Phase Optimization
274. NeurIPS 2025Kernel Learning with Adversarial Features: Numerical Efficiency and Adaptive Regularization
275. NeurIPS 2025Kernel von Mises Formula of the Influence Function
276. NeurIPS 2025Latent Space Factorization in LoRA
277. NeurIPS 2025Learning Robust Vision-Language Models from Natural Latent Spaces
278. NeurIPS 2025LORE: Lagrangian-Optimized Robust Embeddings for Visual Encoders
279. NeurIPS 2025MeCeFO: Enhancing LLM Training Robustness via Fault-Tolerant Optimization
280. NeurIPS 2025MIBP-Cert: Certified Training against Data Perturbations with Mixed-Integer Bilinear Programs
281. NeurIPS 2025MIP against Agent: Malicious Image Patches Hijacking Multimodal OS Agents
282. NeurIPS 2025MixAT: Combining Continuous and Discrete Adversarial Training for LLMs
283. NeurIPS 2025Multi-Environment POMDPs: Discrete Model Uncertainty Under Partial Observability
284. NeurIPS 2025Multimodal Negative Learning
285. NeurIPS 2025No-Regret Learning Under Adversarial Resource Constraints: A Spending Plan Is All You Need!
286. NeurIPS 2025On the Optimality of the Median-of-Means Estimator under Adversarial Contamination
287. NeurIPS 2025On the Robustness of Transformers against Context Hijacking for Linear Classification
288. NeurIPS 2025On the Robustness of Verbal Confidence of LLMs in Adversarial Attacks
289. NeurIPS 2025Optimal Control for Transformer Architectures: Enhancing Generalization, Robustness and Efficiency
290. NeurIPS 2025OSTAR: Optimized Statistical Text-classifier with Adversarial Resistance
291. NeurIPS 2025Parameter-free Algorithms for the Stochastically Extended Adversarial Model
292. NeurIPS 2025PCA++: How Uniformity Induces Robustness to Background Noise in Contrastive Learning
293. NeurIPS 2025Regret Bounds for Adversarial Contextual Bandits with General Function Approximation and Delayed Feedback
294. NeurIPS 2025ReliabilityRAG: Effective and Provably Robust Defense for RAG-based Web-Search
295. NeurIPS 2025Remarkable Robustness of LLMs: Stages of Inference?
296. NeurIPS 2025Reverse Engineering Human Preferences with Reinforcement Learning
297. NeurIPS 2025Robust Equilibria in Continuous Games: From Strategic to Dynamic Robustness
298. NeurIPS 2025Robust learning of halfspaces under log-concave marginals
299. NeurIPS 2025Robust Satisficing Gaussian Process Bandits Under Adversarial Attacks
300. NeurIPS 2025Robust SuperAlignment: Weak-to-Strong Robustness Generalization for Vision-Language Models

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。