1.2k citations · 1.7k across the 17 of their papers we have counts for
17 papers
Give Us the Facts: Enhancing Large Language Models with Knowledge Graphs for Fact-aware Language Modeling
Linyao Yang, Hongyang Chen, Zhao Li +2
Recently, ChatGPT, a representative large language model (LLM), has gained considerable attention due to its powerful emergent abilities. Some researchers suggest that LLMs could p…
Unifying Large Language Models and Knowledge Graphs: A Roadmap
Shirui Pan, Linhao Luo, Yufei Wang +3
Large language models (LLMs), such as ChatGPT and GPT4, are making new waves in the field of natural language processing and artificial intelligence, due to their emergent ability…
A Comprehensive Survey on Automatic Knowledge Graph Construction
Lingfeng Zhong, Jia Wu, Qian Li +2
Automatic knowledge graph construction aims to manufacture structured human knowledge. To this end, much effort has historically been spent extracting informative fact patterns fro…
Towards Efficient Local Causal Structure Learning
Shuai Yang, Hao Wang, Kui Yu +2
Local causal structure learning aims to discover and distinguish direct causes (parents) and direct effects (children) of a variable of interest from data. While emerging successes…
Chinese Lexical Simplification
Jipeng Qiang, Xinyu Lu, Yun Li +3
Lexical simplification has attracted much attention in many languages, which is the process of replacing complex words in a given sentence with simpler alternatives of equivalent m…
LSBert: A Simple Framework for Lexical Simplification
Jipeng Qiang, Yun Li, Yi Zhu +2
Lexical simplification (LS) aims to replace complex words in a given sentence with their simpler alternatives of equivalent meaning, to simplify the sentence. Recently unsupervised…
Causality-based Feature Selection: Methods and Evaluations
Kui Yu, Xianjie Guo, Lin Liu +4
Feature selection is a crucial preprocessing step in data analytics and machine learning. Classical feature selection algorithms select features based on the correlations between p…
Lexical Simplification with Pretrained Encoders
Jipeng Qiang, Yun Li, Yi Zhu +2
Lexical simplification (LS) aims to replace complex words in a given sentence with their simpler alternatives of equivalent meaning. Recently unsupervised lexical simplification ap…
STTM: A Tool for Short Text Topic Modeling
Jipeng Qiang, Yun Li, Yunhao Yuan +2
Along with the emergence and popularity of social communications on the Internet, topic discovery from short texts becomes fundamental to many applications that require semantic un…
Object Detection with Deep Learning: A Review
Zhong-Qiu Zhao, Peng Zheng, Shou-tao Xu +1
Due to object detection's close relationship with video analysis and image understanding, it has attracted much research attention in recent years. Traditional object detection met…
Towards Effective Bug Triage with Towards Effective Bug Triage with Software Data Reduction Techniques
Jifeng Xuan, He Jiang, Yan Hu +4
Software companies spend over 45 percent of cost in dealing with software bugs. An inevitable step of fixing bugs is bug triage, which aims to correctly assign a developer to a new…
Camera Fingerprint: A New Perspective for Identifying User's Identity
Xiang Jiang, Shikui Wei, Ruizhen Zhao +2
Identifying user's identity is a key problem in many data mining applications, such as product recommendation, customized content delivery and criminal identification. Given a set…
Topic Modeling over Short Texts by Incorporating Word Embeddings
Jipeng Qiang, Ping Chen, Tong Wang +1
Inferring topics from the overwhelming amount of short texts becomes a critical but challenging task for many content analysis tasks, such as content charactering, user interest pr…
Online Feature Selection with Group Structure Analysis
Jing Wang, Meng Wang, Peipei Li +4
Online selection of dynamic features has attracted intensive interest in recent years. However, existing online feature selection methods evaluate features individually and ignore…
On the Feasibility of Distributed Kernel Regression for Big Data
Chen Xu, Yongquan Zhang, Runze Li
In modern scientific research, massive datasets with huge numbers of observations are frequently encountered. To facilitate the computational process, a divide-and-conquer scheme i…
NESVM: a Fast Gradient Method for Support Vector Machines
Tianyi Zhou, Dacheng Tao, Xindong Wu
Support vector machines (SVMs) are invaluable tools for many practical applications in artificial intelligence, e.g., classification and event recognition. However, popular SVM sol…
Manifold Elastic Net: A Unified Framework for Sparse Dimension Reduction
Tianyi Zhou, Dacheng Tao, Xindong Wu
It is difficult to find the optimal sparse solution of a manifold learning based dimensionality reduction algorithm. The lasso or the elastic net penalized manifold learning based…