most citedDiffVLA: Vision-Language Guided Diffusion Planning for Autonomous Driving

1 citations · 1 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2026

Plug-and-Play Traffic Element Awareness for End-to-End Autonomous Driving

Zongzheng Zhang, Jijun Wang, Saining Zhang +8

Traffic elements such as traffic lights and road signs play a fundamental role in human driving decisions and should naturally influence end-to-end driving performance. However, ex…

cs.RO2026

UniUncer: Unified Dynamic Static Uncertainty for End to End Driving

Yu Gao, Jijun Wang, Zongzheng Zhang +7

End-to-end (E2E) driving has become a cornerstone of both industry deployment and academic research, offering a single learnable pipeline that maps multi-sensor inputs to actions w…

cs.AI2025

IRL-VLA: Training an Vision-Language-Action Policy via Reward World Model

Anqing Jiang, Yu Gao, Yiru Wang +11

Vision-Language-Action (VLA) models have demonstrated potential in autonomous driving. However, two critical challenges hinder their development: (1) Existing VLA architectures are…

cs.CV2025

DiffSemanticFusion: Semantic Raster BEV Fusion for Autonomous Driving via Online HD Map Diffusion

Zhigang Sun, Yiru Wang, Anqing Jiang +13

Autonomous driving requires accurate scene understanding, including road geometry, traffic agents, and their semantic relationships. In online HD map generation scenarios, raster-b…

cs.AI2025★ 1 cited

DiffVLA: Vision-Language Guided Diffusion Planning for Autonomous Driving

Anqing Jiang, Yu Gao, Zhigang Sun +11

Research interest in end-to-end autonomous driving has surged owing to its fully differentiable design integrating modular tasks, i.e. perception, prediction and planing, which ena…