3 papers
cs.CV2026
Learning Vision-Language-Action World Models for Autonomous Driving
Guoqing Wang, Pin Tang, Xiangxuan Ren +3
Vision-Language-Action (VLA) models have recently achieved notable progress in end-to-end autonomous driving by integrating perception, reasoning, and control within a unified mult…
cs.CV2025
LiteFusion: Taming 3D Object Detectors from Vision-Based to Multi-Modal with Minimal Adaptation
Xiangxuan Ren, Zhongdao Wang, Pin Tang +3
3D object detection is fundamental for safe and robust intelligent transportation systems. Current multi-modal 3D object detectors often rely on complex architectures and training…
cs.CV2025
Grounding Everything in Tokens for Multimodal Large Language Models
Xiangxuan Ren, Zhongdao Wang, Liping Hou +3
Multimodal large language models (MLLMs) have made significant advancements in vision understanding and reasoning. However, the autoregressive Transformer architecture used by MLLM…