26 citations · 104 across the 32 of their papers we have counts for
6 papers · 1 filter
RL-VLA: A Flexible and Asynchronous Reinforcement Learning Framework for VLA Training
Haoran Sun, Yongjian Guo, Zhong Guan +13
Reinforcement learning (RL) has emerged as a critical paradigm for post-training Vision-Language-Action (VLA) models, enabling embodied agents to adapt and improve through environm…
Attention Mechanisms Perspective: Exploring LLM Processing of Graph-Structured Data
Zhong Guan, Likang Wu, Hongke Zhao +2
Attention mechanisms are critical to the success of large language models (LLMs), driving significant advancements in multiple fields. However, for graph-structured data, which req…
LangTopo: Aligning Language Descriptions of Graphs with Tokenized Topological Modeling
Zhong Guan, Hongke Zhao, Likang Wu +2
Recently, large language models (LLMs) have been widely researched in the field of graph machine learning due to their outstanding abilities in language comprehension and learning.…
Exploring Large Language Model for Graph Data Understanding in Online Job Recommendations
Likang Wu, Zhaopeng Qiu, Zhi Zheng +2
Large Language Models (LLMs) have revolutionized natural language processing tasks, demonstrating their exceptional capabilities in various domains. However, their potential for be…
Learning the Implicit Semantic Representation on Graph-Structured Data
Likang Wu, Zhi Li, Hongke Zhao +4
Existing representation learning methods in graph convolutional networks are mainly designed by describing the neighborhood of each node as a perceptual whole, while the implicit s…
Long-term Joint Scheduling for Urban Traffic
Xianfeng Liang, Likang Wu, Joya Chen +7
Recently, the traffic congestion in modern cities has become a growing worry for the residents. As presented in Baidu traffic report, the commuting stress index has reached surpris…