End-to-End Driving papers, 2023–2026

Key findings

• End-to-End Driving went from 33 papers in 2023 to 58 in 2026, roughly 1.8x in three years.
• CVPR publishes the most End-to-End Driving work: 71 papers from 2023 to 2026, 44% of the four-venue total.
• The fastest-growing overlap is with Multimodal LLMs: papers tagged with both rose from 0 in 2023 to 11 in 2026.
• Among the 5 topics under Autonomous Driving, it ranks #5 by 2026 paper count; the fastest grower in the group, Motion Planning, is up 2.4x versus 1.8x here.

Representative papers

Spread across years and venues so every edition shows up

• NeurIPS 2026AlignDrive: Aligned Lateral-Longitudinal Planning for End-to-End Autonomous Driving
• ICML 2026Hide&Seek: Learning to Explain in an End-to-End Differentiable Network
• ICLR 2026RAP: 3D Rasterization Augmented End-to-End Planning
• CVPR 2026Bias at the End of the Score
• NeurIPS 2025Embodied Cognition Augmented End2End Autonomous Driving
• ICML 2025GuidedQuant: Large Language Model Quantization via Exploiting End Loss Guidance
• ICLR 2025MGMapNet: Multi-Granularity Representation Learning for End-to-End Vectorized HD Map Construction
• CVPR 2025Bridging Past and Future: End-to-End Autonomous Driving with Historical Prediction and Planning
• NeurIPS 2024Bench2Drive: Towards Multi-Ability Benchmarking of Closed-Loop End-To-End Autonomous Driving
• ICML 2024Learning Exceptional Subgroups by End-to-End Maximizing KL-Divergence
• ICLR 2024DV-3DLane: End-to-end Multi-modal 3D Lane Detection with Dual-view Representation
• CVPR 2024HIMap: HybrId Representation Learning for End-to-end Vectorized HD Map Construction
• NeurIPS 2023[Re] End-to-end Algorithm Synthesis with Recurrent Networks: Logical Extrapolation Without Overthinking
• ICML 2023End-to-end Differentiable Clustering with Associative Memories
• ICLR 2023E3Bind: An End-to-End Equivariant Network for Protein-Ligand Docking
• CVPR 2023End-to-End Vectorized HD-Map Construction With Piecewise Bezier Curve
• NeurIPS 2026On the Existence of Uniformly Optimal Policies in MDPs under Epistemic Uncertainty
• ICML 2026RoCA: Robust Cross-Domain End-to-End Autonomous Driving
• ICLR 2026THE END OF MANUAL DECODING: TOWARDS TRULY END-TO-END LANGUAGE MODELS
• CVPR 2026LEAD Minimizing Learner-Expert Asymmetry in End-to-End Driving

All End-to-End Driving papers

161 papers, page 3 of 4

101. CVPR 2024Feedback-Guided Autonomous Driving
102. CVPR 2024GaussianAvatars: Photorealistic Head Avatars with Rigged 3D Gaussians
103. CVPR 2024Generalized Predictive Model for Autonomous Driving
104. CVPR 2024Generating Handwritten Mathematical Expressions From Symbol Graphs: An End-to-End Pipeline
105. CVPR 2024HIMap: HybrId Representation Learning for End-to-end Vectorized HD Map Construction
106. CVPR 2024Is Ego Status All You Need for Open-Loop End-to-End Autonomous Driving?
107. CVPR 2024LMDrive: Closed-Loop End-to-End Driving with Large Language Models
108. CVPR 2024NeuRAD: Neural Rendering for Autonomous Driving
109. CVPR 2024On the Road to Portability: Compressing End-to-End Motion Planner for Autonomous Driving
110. CVPR 2024PACER+: On-Demand Pedestrian Animation Controller in Driving Scenarios
111. CVPR 2024PARA-Drive: Parallelized Architecture for Real-time Autonomous Driving
112. CVPR 2024PatchFusion: An End-to-End Tile-Based Framework for High-Resolution Monocular Metric Depth Estimation
113. CVPR 2024PixelRNN: In-pixel Recurrent Neural Networks for End-to-end-optimized Perception with Neural Sensors
114. CVPR 2024SynFog: A Photo-realistic Synthetic Fog Dataset based on End-to-end Imaging Simulation for Advancing Real-World Defogging in Autonomous Driving
115. CVPR 2024Uncertainty-Guided Never-Ending Learning to Drive
116. CVPR 2024UniPAD: A Universal Pre-training Paradigm for Autonomous Driving
117. ICLR 2024DV-3DLane: End-to-end Multi-modal 3D Lane Detection with Dual-view Representation
118. ICML 2024Correcting Diffusion-Based Perceptual Image Compression with Privileged End-to-End Decoder
119. ICML 2024End-to-End Neuro-Symbolic Reinforcement Learning with Textual Explanations
120. ICML 2024Learning Exceptional Subgroups by End-to-End Maximizing KL-Divergence
121. NeurIPS 2024Autonomous Driving with Spiking Neural Networks
122. NeurIPS 2024Bench2Drive: Towards Multi-Ability Benchmarking of Closed-Loop End-To-End Autonomous Driving
123. NeurIPS 2024E2E-MFD: Towards End-to-End Synchronous Multimodal Fusion Detection
124. NeurIPS 2024End-to-End Ontology Learning with Large Language Models
125. NeurIPS 2024Identifying Functionally Important Features with End-to-End Sparse Dictionary Learning
126. NeurIPS 2024Learning to be Smooth: An End-to-End Differentiable Particle Smoother
127. NeurIPS 2024Noisy Label Learning with Instance-Dependent Outliers: Identifiability via Crowd Wisdom
128. NeurIPS 2024OpenCDA-Loop: A Closed-loop Benchmarking Platform for End-to-end Evaluation of Cooperative Perception
129. CVPR 2023Azimuth Super-Resolution for FMCW Radar in Autonomous Driving
130. CVPR 2023BEV-Guided Multi-Modality Fusion for Driving Perception
131. CVPR 2023Dense Distinct Query for End-to-End Object Detection
132. CVPR 2023End-to-End 3D Dense Captioning With Vote2Cap-DETR
133. CVPR 2023End-to-End Vectorized HD-Map Construction With Piecewise Bezier Curve
134. CVPR 2023End-to-End Video Matting With Trimap Propagation
135. CVPR 2023Neural Map Prior for Autonomous Driving
136. CVPR 2023Optimal Proposal Learning for Deployable End-to-End Pedestrian Detection
137. CVPR 2023Planning-Oriented Autonomous Driving
138. CVPR 2023ReasonNet: End-to-End Driving With Temporal and Global Reasoning
139. CVPR 2023Think Twice Before Driving: Towards Scalable Decoders for End-to-End Autonomous Driving
140. CVPR 2023ViP3D: End-to-End Visual Trajectory Prediction via 3D Agent Queries
141. CVPR 2023Weakly Supervised Class-Agnostic Motion Prediction for Autonomous Driving
142. ICLR 2023DINO: DETR with Improved DeNoising Anchor Boxes for End-to-End Object Detection
143. ICLR 2023E3Bind: An End-to-End Equivariant Network for Protein-Ligand Docking
144. ICLR 2023Systematic Rectification of Language Models via Dead-end Analysis
145. ICML 2023Adversarial Policies Beat Superhuman Go AIs
146. ICML 2023End-to-end Differentiable Clustering with Associative Memories
147. ICML 2023End-to-End Full-Atom Antibody Design
148. ICML 2023End-to-end Training of Deep Boltzmann Machines by Unbiased Contrastive Divergence with Local Mode Initialization
149. ICML 2023On the Occupancy Measure of Non-Markovian Policies in Continuous MDPs
150. ICML 2023simple diffusion: End-to-end diffusion for high resolution images

FAQ

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

161 in total: 33 in 2023, 31 in 2024, 39 in 2025, 58 in 2026.

How many End-to-End Driving papers are at NeurIPS 2026?

NeurIPS 2026 has 15 End-to-End Driving papers, versus 18 the year before.

How many End-to-End Driving papers are at ICLR 2026?

ICLR 2026 has 12 End-to-End Driving papers, versus 5 the year before.

How many End-to-End Driving papers are at ICML 2026?

ICML 2026 has 4 End-to-End Driving papers, versus 4 the year before.

How many End-to-End Driving papers are at CVPR 2026?

CVPR 2026 has 27 End-to-End Driving papers, versus 12 the year before.

Which conference publishes the most End-to-End Driving papers?

CVPR, with 71 papers from 2023 to 2026.