16 papers
AcceRL: A Distributed Asynchronous Reinforcement Learning and World Model Framework for Vision-Language-Action Models
Chengxuan Lu, Shukuan Wang, Yanjie Li +10
Reinforcement learning (RL) for large-scale Vision-Language-Action (VLA) models is severely bottlenecked by synchronization barriers and the high cost of environment data acquisiti…
A Graph Foundation Model for Wireless Resource Allocation
Yucheng Sheng, Jiacheng Wang, Le Liang +2
The aggressive densification of modern wireless networks necessitates judicious resource allocation to mitigate severe mutual interference. However, classical iterative algorithms…
Reducing Pilots in Channel Estimation with Predictive Foundation Models
Xingyu Zhou, Le Liang, Hao Ye +3
Accurate channel state information (CSI) acquisition is essential for modern wireless systems, which becomes increasingly difficult under large antenna arrays, strict pilot overhea…
Multimodal-Wireless: A Large-Scale Dataset for Sensing and Communication
Tianhao Mao, Le Liang, Jie Yang +3
This paper presents Multimodal-Wireless, a large-scale open-source dataset for multimodal sensing and communication research. The dataset is generated through an integrated and cus…
CoDS: Collaborative Perception via Digital Semantic Communication
Jipeng Gan, Le Liang, Hua Zhang +2
Semantic communication has been introduced into collaborative perception systems for autonomous driving, offering a promising approach to enhancing data transmission efficiency and…
Cross-Modal Semantic Communication for Heterogeneous Collaborative Perception
Mingyi Lu, Guowei Liu, Le Liang +3
Collaborative perception, an emerging paradigm in autonomous driving, has been introduced to mitigate the limitations of single-vehicle systems, such as limited sensor range and oc…