38 citations · 100 across the 34 of their papers we have counts for
9 papers · 1 filter
Enhancing Temporal Awareness in LLMs for Temporal Point Processes
Lili Chen, Wensheng Gan, Shuang Liang +1
Temporal point processes (TPPs) are crucial for analyzing events over time and are widely used in fields such as finance, healthcare, and social systems. These processes are partic…
Global-focal Adaptation with Information Separation for Noise-robust Transfer Fault Diagnosis
Junyu Ren, Wensheng Gan, Guangyu Zhang +2
Existing transfer fault diagnosis methods typically assume either clean data or sufficient domain similarity, which limits their effectiveness in industrial environments where seve…
Advances in Large Language Models for Medicine
Zhiyu Kan, Wensheng Gan, Zhenlian Qi +1
Artificial intelligence (AI) technology has advanced rapidly in recent years, with large language models (LLMs) emerging as a significant breakthrough. LLMs are increasingly making…
ADKGD: Anomaly Detection in Knowledge Graphs with Dual-Channel Training
Jiayang Wu, Wensheng Gan, Jiahao Zhang +1
In the current development of large language models (LLMs), it is important to ensure the accuracy and reliability of the underlying data sources. LLMs are critical for various app…
Artificial Intelligence in Landscape Architecture: A Survey
Yue Xing, Wensheng Gan, Qidi Chen
The development history of landscape architecture (LA) reflects the human pursuit of environmental beautification and ecological balance. With the advancement of artificial intelli…
Multimodal Large Language Models: A Survey
Jiayang Wu, Wensheng Gan, Zefeng Chen +2
The exploration of multimodal language models integrates multiple data types, such as images, text, language, audio, and other heterogeneity. While the latest large language models…
Large Language Models in Education: Vision and Opportunities
Wensheng Gan, Zhenlian Qi, Jiayang Wu +1
With the rapid development of artificial intelligence technology, large language models (LLMs) have become a hot research topic. Education plays an important role in human social d…
Model-as-a-Service (MaaS): A Survey
Wensheng Gan, Shicheng Wan, Philip S. Yu
Due to the increased number of parameters and data in the pre-trained model exceeding a certain level, a foundation model (e.g., a large language model) can significantly improve d…
Discovering Utility-driven Interval Rules
Chunkai Zhang, Maohua Lyu, Huaijin Hao +2
For artificial intelligence, high-utility sequential rule mining (HUSRM) is a knowledge discovery method that can reveal the associations between events in the sequences. Recently,…