Simulation for Driving papers, 2023–2026

Key findings

• Simulation for Driving went from 969 papers in 2023 to 2,200 in 2026, roughly 2.3x in three years.
• NeurIPS publishes the most Simulation for Driving work: 2,111 papers from 2023 to 2026, 36% of the four-venue total.
• The fastest-growing overlap is with Diffusion Models: papers tagged with both rose from 27 in 2023 to 205 in 2026.
• Among the 5 topics under Autonomous Driving, it ranks #1 by 2026 paper count; the fastest grower in the group, Motion Planning, is up 2.4x versus 2.3x here.

Representative papers

Spread across years and venues so every edition shows up

• 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

All Simulation for Driving papers

358 papers, page 6 of 8

251. ICML 2024Polynomial-based Self-Attention for Table Representation Learning
252. ICML 2024Position: A Call for Embodied AI
253. ICML 2024Position: Building Guardrails for Large Language Models Requires Systematic Design
254. ICML 2024Position: Considerations for Differentially Private Learning with Large-Scale Public Pretraining
255. ICML 2024Position: Data Authenticity, Consent, & Provenance for AI are all broken: what will it take to fix them?
256. ICML 2024Position: Intent-aligned AI Systems Must Optimize for Agency Preservation
257. ICML 2024Position: Is machine learning good or bad for the natural sciences?
258. ICML 2024Position: Levels of AGI for Operationalizing Progress on the Path to AGI
259. ICML 2024Position: Open-Endedness is Essential for Artificial Superhuman Intelligence
260. ICML 2024Position: Opportunities Exist for Machine Learning in Magnetic Fusion Energy
261. ICML 2024Position: Rethinking Post-Hoc Search-Based Neural Approaches for Solving Large-Scale Traveling Salesman Problems
262. ICML 2024Position: Scaling Simulation is Neither Necessary Nor Sufficient for In-the-Wild Robot Manipulation
263. ICML 2024Position: Social Environment Design Should be Further Developed for AI-based Policy-Making
264. ICML 2024Position: Standardization of Behavioral Use Clauses is Necessary for the Adoption of Responsible Licensing of AI
265. ICML 2024Position: Tensor Networks are a Valuable Asset for Green AI
266. ICML 2024Position: The Reasonable Person Standard for AI
267. ICML 2024Position: Topological Deep Learning is the New Frontier for Relational Learning
268. ICML 2024Position: Video as the New Language for Real-World Decision Making
269. ICML 2024Practical Performance Guarantees for Pipelined DNN Inference
270. ICML 2024Predicting Lagrangian Multipliers for Mixed Integer Linear Programs
271. ICML 2024Predictive Linear Online Tracking for Unknown Targets
272. ICML 2024PriorBoost: An Adaptive Algorithm for Learning from Aggregate Responses
273. ICML 2024PRISE: LLM-Style Sequence Compression for Learning Temporal Action Abstractions in Control
274. ICML 2024Proactive DP: A Multiple Target Optimization Framework for DP-SGD
275. ICML 2024Projection-Free Variance Reduction Methods for Stochastic Constrained Multi-Level Compositional Optimization
276. ICML 2024Prompt Sketching for Large Language Models
277. ICML 2024Prompt-tuning Latent Diffusion Models for Inverse Problems
278. ICML 2024Prospective Side Information for Latent MDPs
279. ICML 2024Prospector Heads: Generalized Feature Attribution for Large Models & Data
280. ICML 2024ProtoGate: Prototype-based Neural Networks with Global-to-local Feature Selection for Tabular Biomedical Data
281. ICML 2024Provable Benefits of Local Steps in Heterogeneous Federated Learning for Neural Networks: A Feature Learning Perspective
282. ICML 2024Pruner-Zero: Evolving Symbolic Pruning Metric From Scratch for Large Language Models
283. ICML 2024Q-Probe: A Lightweight Approach to Reward Maximization for Language Models
284. ICML 2024Q-value Regularized Transformer for Offline Reinforcement Learning
285. ICML 2024QBMK: Quantum-based Matching Kernels for Un-attributed Graphs
286. ICML 2024Quantum Positional Encodings for Graph Neural Networks
287. ICML 2024Quasi-Monte Carlo Features for Kernel Approximation
288. ICML 2024QuRating: Selecting High-Quality Data for Training Language Models
289. ICML 2024Randomized Confidence Bounds for Stochastic Partial Monitoring
290. ICML 2024Reason for Future, Act for Now: A Principled Architecture for Autonomous LLM Agents
291. ICML 2024Recurrent Early Exits for Federated Learning with Heterogeneous Clients
292. ICML 2024Relaxing the Accurate Imputation Assumption in Doubly Robust Learning for Debiased Collaborative Filtering
293. ICML 2024ReLUs Are Sufficient for Learning Implicit Neural Representations
294. ICML 2024REMEDI: Corrective Transformations for Improved Neural Entropy Estimation
295. ICML 2024Reservoir Computing for Short High-Dimensional Time Series: an Application to SARS-CoV-2 Hospitalization Forecast
296. ICML 2024Restoring balance: principled under/oversampling of data for optimal classification
297. ICML 2024Revisiting the Power of Prompt for Visual Tuning
298. ICML 2024Reweighted Solutions for Weighted Low Rank Approximation
299. ICML 2024RigorLLM: Resilient Guardrails for Large Language Models against Undesired Content
300. ICML 2024RoboDreamer: Learning Compositional World Models for Robot Imagination

FAQ

How many Simulation for Driving papers were published at NeurIPS, ICLR, ICML and CVPR from 2023 to 2026?

5,882 in total: 969 in 2023, 1,308 in 2024, 1,405 in 2025, 2,200 in 2026.

How many Simulation for Driving papers are at NeurIPS 2026?

NeurIPS 2026 has 940 Simulation for Driving papers, versus 542 the year before.

How many Simulation for Driving papers are at ICLR 2026?

ICLR 2026 has 313 Simulation for Driving papers, versus 228 the year before.

How many Simulation for Driving papers are at ICML 2026?

ICML 2026 has 363 Simulation for Driving papers, versus 275 the year before.

How many Simulation for Driving papers are at CVPR 2026?

CVPR 2026 has 584 Simulation for Driving papers, versus 360 the year before.

Which conference publishes the most Simulation for Driving papers?

NeurIPS, with 2,111 papers from 2023 to 2026.