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 331 篇,第 3 / 7 页
- ICLR 2025Adversarial Perturbations Cannot Reliably Protect Artists From Generative AI
- ICLR 2025Adversarial Score identity Distillation: Rapidly Surpassing the Teacher in One Step
- ICLR 2025Adversarial Search Engine Optimization for Large Language Models
- ICLR 2025Adversarial Training Can Provably Improve Robustness: Theoretical Analysis of Feature Learning Process Under Structured Data
- ICLR 2025Adversarial Training for Defense Against Label Poisoning Attacks
- ICLR 2025Adversarially Robust Out-of-Distribution Detection Using Lyapunov-Stabilized Embeddings
- ICLR 2025Adversaries With Incentives: A Strategic Alternative to Adversarial Robustness
- ICLR 2025AdvPaint: Protecting Images from Inpainting Manipulation via Adversarial Attention Disruption
- ICLR 2025AgentHarm: A Benchmark for Measuring Harmfulness of LLM Agents
- ICLR 2025Algorithmic Stability Based Generalization Bounds for Adversarial Training
- ICLR 2025Aligned LLMs Are Not Aligned Browser Agents
- ICLR 2025Artificial Kuramoto Oscillatory Neurons
- ICLR 2025ASTrA: Adversarial Self-supervised Training with Adaptive-Attacks
- ICLR 2025Beyond Interpretability: The Gains of Feature Monosemanticity on Model Robustness
- ICLR 2025Boosting the visual interpretability of CLIP via adversarial fine-tuning
- ICLR 2025Certified Robustness Under Bounded Levenshtein Distance
- ICLR 2025CLIPure: Purification in Latent Space via CLIP for Adversarially Robust Zero-Shot Classification
- ICLR 2025Confidence Elicitation: A New Attack Vector for Large Language Models
- ICLR 2025Deep MMD Gradient Flow without adversarial training
- ICLR 2025Democratic Training Against Universal Adversarial Perturbations
- ICLR 2025Diffusion State-Guided Projected Gradient for Inverse Problems
- ICLR 2025Dissecting Adversarial Robustness of Multimodal LM Agents
- ICLR 2025Does Refusal Training in LLMs Generalize to the Past Tense?
- ICLR 2025DRoP: Distributionally Robust Data Pruning
- ICLR 2025Endless Jailbreaks with Bijection Learning
- ICLR 2025Endowing Visual Reprogramming with Adversarial Robustness
- ICLR 2025Enhancing Prediction Performance through Influence Measure
- ICLR 2025Enhancing Robust Fairness via Confusional Spectral Regularization
- ICLR 2025Estimating the Probabilities of Rare Outputs in Language Models
- ICLR 2025Exact Certification of (Graph) Neural Networks Against Label Poisoning
- ICLR 2025Exploring The Forgetting in Adversarial Training: A Novel Method for Enhancing Robustness
- ICLR 2025Failures to Find Transferable Image Jailbreaks Between Vision-Language Models
- ICLR 2025Feature Averaging: An Implicit Bias of Gradient Descent Leading to Non-Robustness in Neural Networks
- ICLR 2025GOttack: Universal Adversarial Attacks on Graph Neural Networks via Graph Orbits Learning
- ICLR 2025GPromptShield: Elevating Resilience in Graph Prompt Tuning Against Adversarial Attacks
- ICLR 2025GSBA$^K$: $top$-$K$ Geometric Score-based Black-box Attack
- ICLR 2025Improved Diffusion-based Generative Model with Better Adversarial Robustness
- ICLR 2025Improving Generalization and Robustness in SNNs Through Signed Rate Encoding and Sparse Encoding Attacks
- ICLR 2025Indirect Gradient Matching for Adversarial Robust Distillation
- ICLR 2025Input Space Mode Connectivity in Deep Neural Networks
- ICLR 2025Is Your Multimodal Language Model Oversensitive to Safe Queries?
- ICLR 2025Jailbreaking as a Reward Misspecification Problem
- ICLR 2025Jailbreaking Leading Safety-Aligned LLMs with Simple Adaptive Attacks
- ICLR 2025Learning Randomized Algorithms with Transformers
- ICLR 2025Long-tailed Adversarial Training with Self-Distillation
- ICLR 2025Measuring Non-Adversarial Reproduction of Training Data in Large Language Models
- ICLR 2025Minimax Optimal Two-Stage Algorithm For Moment Estimation Under Covariate Shift
- ICLR 2025MixMax: Distributional Robustness in Function Space via Optimal Data Mixtures
- ICLR 2025Model-Free Offline Reinforcement Learning with Enhanced Robustness
- ICLR 2025Multi-level Certified Defense Against Poisoning Attacks in Offline Reinforcement Learning
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。