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20242026
most citedA Survey on Vision-Language-Action Models for Autonomous Driving

2 citations · 2 across the 8 of their papers we have counts for

collaborators

8 papers

cs.RO2026

Factor-Aware Mixture-of-Experts with Pretrained Encoder for Combinatorial Generalization

Feihong Zhang, Guojian Zhan, Zeyu He +8

The integration of pretrained encoders with diffusion policies has become a dominant paradigm for visual robotic manipulation. However, it still struggles to generalize across comp…

cs.CV2026

HarmoGS: Robust 3D Gaussian Splatting in the Wild via Conflict-Aware Gradient Harmonization

Yulei Kang, Tianze Zhu, Jian-Fang Hu +2

In-the-wild 3D Gaussian Splatting remains challenging due to transient distractors and illumination-induced cross-view appearance inconsistencies. Existing methods mainly rely on i…

cs.LG2026

Real-Time Generative Policy via Langevin-Guided Flow Matching for Autonomous Driving

Tianze Zhu, Yinuo Wang, Wenjun Zou +6

Reinforcement learning (RL) is a fundamental methodology in autonomous driving systems, where generative policies exhibit considerable potential by leveraging their ability to mode…

cs.CV2025★ 2 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.LG2025

Enhanced DACER Algorithm with High Diffusion Efficiency

Yinuo Wang, Likun Wang, Mining Tan +11

Due to their expressive capacity, diffusion models have shown great promise in offline RL and imitation learning. Diffusion Actor-Critic with Entropy Regulator (DACER) extended thi…

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…