most citedA Survey on Vision-Language-Action Models for Autonomous Driving

2 citations · 2 across the 7 of their papers we have counts for

collaborators

16 papers

cs.RO2025

MTRDrive: Memory-Tool Synergistic Reasoning for Robust Autonomous Driving in Corner Cases

Ziang Luo, Kangan Qian, Jiahua Wang +13

Vision-Language Models(VLMs) have demonstrated significant potential for end-to-end autonomous driving, yet a substantial gap remains between their current capabilities and the rel…

cs.CV2025

Realistic and Controllable 3D Gaussian-Guided Object Editing for Driving Video Generation

Jiusi Li, Jackson Jiang, Jinyu Miao +10

Corner cases are crucial for training and validating autonomous driving systems, yet collecting them from the real world is often costly and hazardous. Editing objects within captu…

cs.LG2025

EvaDrive: Evolutionary Adversarial Policy Optimization for End-to-End Autonomous Driving

Siwen Jiao, Kangan Qian, Hao Ye +12

Autonomous driving faces significant challenges in achieving human-like iterative decision-making, which continuously generates, evaluates, and refines trajectory proposals. Curren…

cs.CV20252 cited

A Survey on Vision-Language-Action Models for Autonomous Driving

Sicong Jiang, Zilin Huang, Kangan Qian +17

The rapid progress of multimodal large language models (MLLM) has paved the way for Vision-Language-Action (VLA) paradigms, which integrate visual perception, natural language unde…

cs.CV2025

COME: Adding Scene-Centric Forecasting Control to Occupancy World Model

Yining Shi, Kun Jiang, Qiang Meng +6

World models are critical for autonomous driving to simulate environmental dynamics and generate synthetic data. Existing methods struggle to disentangle ego-vehicle motion (perspe…

cs.RO2025

AgentThink: A Unified Framework for Tool-Augmented Chain-of-Thought Reasoning in Vision-Language Models for Autonomous Driving

Kangan Qian, Sicong Jiang, Yang Zhong +18

Vision-Language Models (VLMs) show promise for autonomous driving, yet their struggle with hallucinations, inefficient reasoning, and limited real-world validation hinders accurate…