20 citations · 47 across the 5 of their papers we have counts for
5 papers
MLDT: Multi-Level Decomposition for Complex Long-Horizon Robotic Task Planning with Open-Source Large Language Model
Yike Wu, Jiatao Zhang, Nan Hu +5
In the realm of data-driven AI technology, the application of open-source large language models (LLMs) in robotic task planning represents a significant milestone. Recent robotic t…
The Role of LLMs in Sustainable Smart Cities: Applications, Challenges, and Future Directions
Amin Ullah, Guilin Qi, Saddam Hussain +2
Smart cities stand as pivotal components in the ongoing pursuit of elevating urban living standards, facilitating the rapid expansion of urban areas while efficiently managing reso…
Exploring the Impact of Table-to-Text Methods on Augmenting LLM-based Question Answering with Domain Hybrid Data
Dehai Min, Nan Hu, Rihui Jin +8
Augmenting Large Language Models (LLMs) for Question Answering (QA) with domain specific data has attracted wide attention. However, domain data often exists in a hybrid format, in…
Retrieve-Rewrite-Answer: A KG-to-Text Enhanced LLMs Framework for Knowledge Graph Question Answering
Yike Wu, Nan Hu, Sheng Bi +4
Despite their competitive performance on knowledge-intensive tasks, large language models (LLMs) still have limitations in memorizing all world knowledge especially long tail knowl…
Merging Knowledge Bases in Possibilistic Logic by Lexicographic Aggregation
Guilin Qi, Jianfeng Du, Weiru Liu +1
Belief merging is an important but difficult problem in Artificial Intelligence, especially when sources of information are pervaded with uncertainty. Many merging operators have b…