2 citations · 2 across the 8 of their papers we have counts for
8 papers
LIRA: Local Cross-Layer Information Routing for Vision-Language-Action Decoding
Zhewei Zhang, Puyue Wang, Guanren Qiao +10
Vision-Language-Action (VLA) models transform representations from pretrained vision-language models (VLMs) into robot actions, yet the interface that routes intermediate VLM featu…
PLAN-S: Bridging Planning with Latent Style Dynamics for Autonomous Driving World Models
Xiaoyun Qiu, Jingtao He, Yijie Chen +4
Latent world models (LWMs) have strengthened end-to-end autonomous driving by forecasting compact scene dynamics for downstream planning. However, existing LWM-based planners usual…
Potential-Guided Flow Matching for Vision-Language-Action Policy Improvement
Yunpeng Mei, Jiakai He, Hongjie Cao +12
Large vision-language-action (VLA) policies are increasingly trained as conditional generative models over action chunks. Yet deployment produces mixed-quality experience-successfu…
High-resolution urban air pollution and thermal comfort mapping: an application of drive mobile sensing platform for smart city services
Hui Zhong, Hongliang Lu, Ting Gan +2
Air pollutant exposure exhibits significant spatial and temporal variability, with localized hotspots, particularly in traffic microenvironments, posing health risks to commuters.…
Continual Learning for Adaptable Car-Following in Dynamic Traffic Environments
Xianda Chen, PakHin Tiu, Xu Han +4
The continual evolution of autonomous driving technology requires car-following models that can adapt to diverse and dynamic traffic environments. Traditional learning-based models…
CAV-AHDV-CAV: Mitigating Traffic Oscillations for CAVs through a Novel Car-Following Structure and Reinforcement Learning
Xianda Chen, PakHin Tiu, Yihuai Zhang +2
Connected and Automated Vehicles (CAVs) offer a promising solution to the challenges of mixed traffic with both CAVs and Human-Driven Vehicles (HDVs). A significant hurdle in such…