驾驶仿真论文趋势 2023–2026

主要结论

• 驾驶仿真论文从 2023 年的 969 篇增长到 2026 年的 2,200 篇，三年间扩大到约 2.3 倍。
• NeurIPS 是发驾驶仿真论文最多的会议，2023–2026 年共 2,111 篇，占四个会议总量的 36%。
• 交叉方向里涨得最快的是扩散模型：同时属于两个主题的论文从 2023 年的 27 篇增至 2026 年的 205 篇。
• 在「自动驾驶」的 5 个主题里，它的 2026 年论文数排第 1；同组增长最快的运动规划是 2.4 倍，驾驶仿真是 2.3 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 2026$SE(2)$-Aware Conditional Distribution Transport for Vehicle Trajectory Generation
• ICML 2026A Penalty Approach For Differentiation Through Black-box Quadratic Programming Solvers
• ICLR 2026A Schrödinger Eigenfunction Method for Long-Horizon Stochastic Optimal Control
• CVPR 2026A2GC Asymmetric Aggregation with Geometric Constraints for Locally Aggregated Descriptors
• NeurIPS 2025A compressive-expressive communication framework for compositional representations
• ICML 2025A Near-Optimal Single-Loop Stochastic Algorithm for Convex Finite-Sum Coupled Compositional Optimization
• ICLR 2025A Truncated Newton Method for Optimal Transport
• CVPR 20253D-SLNR: A Super Lightweight Neural Representation for Large-scale 3D Mapping
• NeurIPS 2024[Re] CUDA: Curriculum of Data Augmentation for Long‐tailed Recognition
• ICML 2024$H$-Consistency Guarantees for Regression
• ICLR 2024$\texttt{NAISR}$: A 3D Neural Additive Model for Interpretable Shape Representation
• CVPR 2024Decentralized Directed Collaboration for Personalized Federated Learning
• NeurIPS 2023[Re] FOCUS: Flexible Optimizable Counterfactual Explanations for Tree Ensembles
• ICML 2023$H$-Consistency Bounds for Pairwise Misranking Loss Surrogates
• ICLR 2023A Convergent Single-Loop Algorithm for Relaxation of Gromov-Wasserstein in Graph Data
• CVPR 20233DAvatarGAN: Bridging Domains for Personalized Editable Avatars
• NeurIPS 2026A Bitter Lesson for Data Filtering
• ICML 2026A Queueing-Theoretic Framework for Stability Analysis of LLM Inference with KV Cache Memory Constraints
• ICLR 2026Bayesian Neural Networks for Functional ANOVA Model
• CVPR 2026Active Perceptual Inference A Corticothalamic-Inspired Dynamic Nested Recurrent Network for

全部驾驶仿真论文

共 410 篇，第 2 / 9 页

51. NeurIPS 2024Approximately Pareto-optimal Solutions for Bi-Objective k-Clustering
52. NeurIPS 2024Are Large-scale Soft Labels Necessary for Large-scale Dataset Distillation?
53. NeurIPS 2024Are Multiple Instance Learning Algorithms Learnable for Instances?
54. NeurIPS 2024Assemblage: Automatic Binary Dataset Construction for Machine Learning
55. NeurIPS 2024Atlas3D: Physically Constrained Self-Supporting Text-to-3D for Simulation and Fabrication
56. NeurIPS 2024Average gradient outer product as a mechanism for deep neural collapse
57. NeurIPS 2024Banded Square Root Matrix Factorization for Differentially Private Model Training
58. NeurIPS 2024BehaviorGPT: Smart Agent Simulation for Autonomous Driving with Next-Patch Prediction
59. NeurIPS 2024Belief-State Query Policies for User-Aligned POMDPs
60. NeurIPS 2024Bench2Drive: Towards Multi-Ability Benchmarking of Closed-Loop End-To-End Autonomous Driving
61. NeurIPS 2024Benchmark Data Repositories for Better Benchmarking
62. NeurIPS 2024Benchmarking Out-of-Distribution Generalization Capabilities of DNN-based Encoding Models for the Ventral Visual Cortex.
63. NeurIPS 2024Benchmarking Uncertainty Disentanglement: Specialized Uncertainties for Specialized Tasks
64. NeurIPS 2024BiDM: Pushing the Limit of Quantization for Diffusion Models
65. NeurIPS 2024BMRS: Bayesian Model Reduction for Structured Pruning
66. NeurIPS 2024Boundary Decomposition for Nadir Objective Vector Estimation
67. NeurIPS 2024Bounds for the smallest eigenvalue of the NTK for arbitrary spherical data of arbitrary dimension
68. NeurIPS 2024Cascade Speculative Drafting for Even Faster LLM Inference
69. NeurIPS 2024Causal Inference in the Closed-Loop: Marginal Structural Models for Sequential Excursion Effects
70. NeurIPS 2024Certified Adversarial Robustness via Randomized $\alpha$-Smoothing for Regression Models
71. NeurIPS 2024Certified Robustness for Deep Equilibrium Models via Serialized Random Smoothing
72. NeurIPS 2024CiteME: Can Language Models Accurately Cite Scientific Claims?
73. NeurIPS 2024Classic GNNs are Strong Baselines: Reassessing GNNs for Node Classification
74. NeurIPS 2024Classifier-guided Gradient Modulation for Enhanced Multimodal Learning
75. NeurIPS 2024CLIPAway: Harmonizing focused embeddings for removing objects via diffusion models
76. NeurIPS 2024Closed-Loop Visuomotor Control with Generative Expectation for Robotic Manipulation
77. NeurIPS 2024Coded Computing for Resilient Distributed Computing: A Learning-Theoretic Framework
78. NeurIPS 2024CoIN: A Benchmark of Continual Instruction Tuning for Multimodel Large Language Models
79. NeurIPS 2024Collaboration! Towards Robust Neural Methods for Routing Problems
80. NeurIPS 2024Collaborative Refining for Learning from Inaccurate Labels
81. NeurIPS 2024CoLoR-Filter: Conditional Loss Reduction Filtering for Targeted Language Model Pre-training
82. NeurIPS 2024ComBack: A Versatile Dataset for Enhancing Compiler Backend Development Efficiency
83. NeurIPS 2024Compositional Automata Embeddings for Goal-Conditioned Reinforcement Learning
84. NeurIPS 2024Conformal Classification with Equalized Coverage for Adaptively Selected Groups
85. NeurIPS 2024Connectivity Shapes Implicit Regularization in Matrix Factorization Models for Matrix Completion
86. NeurIPS 2024Consensus Learning with Deep Sets for Essential Matrix Estimation
87. NeurIPS 2024Consistency Models for Scalable and Fast Simulation-Based Inference
88. NeurIPS 2024Convergence of $\text{log}(1/\epsilon)$ for Gradient-Based Algorithms in Zero-Sum Games without the Condition Number: A Smoothed Analysis
89. NeurIPS 2024Counter-Current Learning: A Biologically Plausible Dual Network Approach for Deep Learning
90. NeurIPS 2024Crafting Interpretable Embeddings for Language Neuroscience by Asking LLMs Questions
91. NeurIPS 2024Credal Deep Ensembles for Uncertainty Quantification
92. NeurIPS 2024Croissant: A Metadata Format for ML-Ready Datasets
93. NeurIPS 2024CryoBench: Diverse and challenging datasets for the heterogeneity problem in cryo-EM
94. NeurIPS 2024CTIBench: A Benchmark for Evaluating LLMs in Cyber Threat Intelligence
95. NeurIPS 2024D-LLM: A Token Adaptive Computing Resource Allocation Strategy for Large Language Models
96. NeurIPS 2024DAGER: Exact Gradient Inversion for Large Language Models
97. NeurIPS 2024DARNet: Dual Attention Refinement Network with Spatiotemporal Construction for Auditory Attention Detection
98. NeurIPS 2024Data subsampling for Poisson regression with pth-root-link
99. NeurIPS 2024DC-Gaussian: Improving 3D Gaussian Splatting for Reflective Dash Cam Videos
100. NeurIPS 2024DDGS-CT: Direction-Disentangled Gaussian Splatting for Realistic Volume Rendering

常见问题

2023–2026 年四大会议一共有多少篇驾驶仿真论文？

共 5,882 篇，按年份分别是 2023 年 969 篇、2024 年 1,308 篇、2025 年 1,405 篇、2026 年 2,200 篇。

NeurIPS 2026 有多少篇驾驶仿真论文？

NeurIPS 2026 有 940 篇驾驶仿真论文，上一届是 542 篇。

ICLR 2026 有多少篇驾驶仿真论文？

ICLR 2026 有 313 篇驾驶仿真论文，上一届是 228 篇。

ICML 2026 有多少篇驾驶仿真论文？

ICML 2026 有 363 篇驾驶仿真论文，上一届是 275 篇。

CVPR 2026 有多少篇驾驶仿真论文？

CVPR 2026 有 584 篇驾驶仿真论文，上一届是 360 篇。

哪个会议的驾驶仿真论文最多？

NeurIPS，2023–2026 年共 2,111 篇。