驾驶仿真论文趋势 2023–2026

闭环仿真

统计范围：NeurIPS、ICLR、ICML、CVPR 四个会议，2023–2026 年，共 5,882 篇被归入该主题的论文。

主要结论

每年论文数

各会议论文数

按年份和会议统计

驾驶仿真论文数，按年份和会议
年份NeurIPSICLRICMLCVPR合计
2023219182218350969
20244101763583641,308
20255422282753601,405
20269403133635842,200

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

全部驾驶仿真论文

年份全部2023202420252026
会议全部NeurIPSICLRICMLCVPR

共 358 篇，第 7 / 8 页

  1. ICML 2024RoboGen: Towards Unleashing Infinite Data for Automated Robot Learning via Generative Simulation
  2. ICML 2024Robust Sparse Estimation for Gaussians with Optimal Error under Huber Contamination
  3. ICML 2024Robustness of Deep Learning for Accelerated MRI: Benefits of Diverse Training Data
  4. ICML 2024Sample Complexity Bounds for Estimating Probability Divergences under Invariances
  5. ICML 2024Sample-specific Masks for Visual Reprogramming-based Prompting
  6. ICML 2024Sampling is as easy as keeping the consistency: convergence guarantee for Consistency Models
  7. ICML 2024Scaling Laws for the Value of Individual Data Points in Machine Learning
  8. ICML 2024Seesaw: Compensating for Nonlinear Reduction with Linear Computations for Private Inference
  9. ICML 2024Sign is Not a Remedy: Multiset-to-Multiset Message Passing for Learning on Heterophilic Graphs
  10. ICML 2024Simple Ingredients for Offline Reinforcement Learning
  11. ICML 2024Simulation of Graph Algorithms with Looped Transformers
  12. ICML 2024Simulation-Based Inference with Quantile Regression
  13. ICML 2024SiT: Symmetry-invariant Transformers for Generalisation in Reinforcement Learning
  14. ICML 2024Slicing Mutual Information Generalization Bounds for Neural Networks
  15. ICML 2024SPADE: Sparsity-Guided Debugging for Deep Neural Networks
  16. ICML 2024Sparse-IFT: Sparse Iso-FLOP Transformations for Maximizing Training Efficiency
  17. ICML 2024Spectral Preconditioning for Gradient Methods on Graded Non-convex Functions
  18. ICML 2024Spider: A Unified Framework for Context-dependent Concept Segmentation
  19. ICML 2024Spike Distance Function as a Learning Objective for Spike Prediction
  20. ICML 2024SpikeZIP-TF: Conversion is All You Need for Transformer-based SNN
  21. ICML 2024Stochastic Q-learning for Large Discrete Action Spaces
  22. ICML 2024Stop Regressing: Training Value Functions via Classification for Scalable Deep RL
  23. ICML 2024Submodular framework for structured-sparse optimal transport
  24. ICML 2024Subsampling is not Magic: Why Large Batch Sizes Work for Differentially Private Stochastic Optimisation
  25. ICML 2024SyCoCa: Symmetrizing Contrastive Captioners with Attentive Masking for Multimodal Alignment
  26. ICML 2024Tandem Transformers for Inference Efficient LLMs
  27. ICML 2024Taylor Videos for Action Recognition
  28. ICML 2024TENG: Time-Evolving Natural Gradient for Solving PDEs With Deep Neural Nets Toward Machine Precision
  29. ICML 2024TERD: A Unified Framework for Safeguarding Diffusion Models Against Backdoors
  30. ICML 2024The Benefits of Reusing Batches for Gradient Descent in Two-Layer Networks: Breaking the Curse of Information and Leap Exponents
  31. ICML 2024The Merit of River Network Topology for Neural Flood Forecasting
  32. ICML 2024Theoretical Guarantees for Variational Inference with Fixed-Variance Mixture of Gaussians
  33. ICML 2024Thermometer: Towards Universal Calibration for Large Language Models
  34. ICML 2024TIC-TAC: A Framework For Improved Covariance Estimation In Deep Heteroscedastic Regression
  35. ICML 2024Total Variation Floodgate for Variable Importance Inference in Classification
  36. ICML 2024Towards Certified Unlearning for Deep Neural Networks
  37. ICML 2024Towards Realistic Model Selection for Semi-supervised Learning
  38. ICML 2024Trainable Transformer in Transformer
  39. ICML 2024Training Large Language Models for Reasoning through Reverse Curriculum Reinforcement Learning
  40. ICML 2024Triple Changes Estimator for Targeted Policies
  41. ICML 2024Tripod: Three Complementary Inductive Biases for Disentangled Representation Learning
  42. ICML 2024Trust Regions for Explanations via Black-Box Probabilistic Certification
  43. ICML 2024TSLANet: Rethinking Transformers for Time Series Representation Learning
  44. ICML 2024Two Stones Hit One Bird: Bilevel Positional Encoding for Better Length Extrapolation
  45. ICML 2024ULAREF: A Unified Label Refinement Framework for Learning with Inaccurate Supervision
  46. ICML 2024Uncertainty for Active Learning on Graphs
  47. ICML 2024Unveiling the Potential of AI for Nanomaterial Morphology Prediction
  48. ICML 2024Variance-reduced Zeroth-Order Methods for Fine-Tuning Language Models
  49. ICML 2024Variational Inference with Coverage Guarantees in Simulation-Based Inference
  50. ICML 2024Variational Learning is Effective for Large Deep Networks

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 查驾驶仿真在 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": "simulation-for-driving"}

两分钟接入 Paperlist MCP（Claude Code、Cursor、Codex、ChatGPT）

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。

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