38 citations · 100 across the 34 of their papers we have counts for
36 papers
DeepSeek Robustness Against Semantic-Character Dual-Space Mutated Prompt Injection
Junyu Ren, Xingjian Pan, Wensheng Gan +1
Prompt injection has emerged as a critical security threat to large language models (LLMs), yet existing studies predominantly focus on single-dimensional attack strategies, such a…
UPER: Efficient Utility-driven Partially-ordered Episode Rule Mining
Hong Lin, Wensheng Gan, Junyu Ren +1
Episode mining is a fundamental problem in analyzing a sequence of numerous events. For discovering strong relationships between events in a complex event sequence, episode rule mi…
Guided Exploration of Sequential Rules
Wensheng Gan, Gengsen Huang, Junyu Ren +1
In pattern mining, sequential rules provide a formal framework to capture the temporal relationships and inferential dependencies between items. However, the discovery process is c…
High-utility Sequential Rule Mining Utilizing Segmentation Guided by Confidence
Chunkai Zhang, Jiarui Deng, Maohua Lyu +2
Within the domain of data mining, one critical objective is the discovery of sequential rules with high utility. The goal is to discover sequential rules that exhibit both high uti…
Discovering High-utility Sequential Rules with Increasing Utility Ratio
Zhenqiang Ye, Wensheng Gan, Gengsen Huang +2
Utility-driven mining is an essential task in data science, as it can provide deeper insight into the real world. High-utility sequential rule mining (HUSRM) aims at discovering se…
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…
Graph Attention-based Adaptive Transfer Learning for Link Prediction
Huashen Lu, Wensheng Gan, Guoting Chen +2
Graph neural networks (GNNs) have brought revolutionary advancements to the field of link prediction (LP), providing powerful tools for mining potential relationships in graphs. Ho…
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…
Pure Node Selection for Imbalanced Graph Node Classification
Fanlong Zeng, Wensheng Gan, Jiayang Wu +1
The problem of class imbalance refers to an uneven distribution of quantity among classes in a dataset, where some classes are significantly underrepresented compared to others. Cl…
GraphIFE: Rethinking Graph Imbalance Node Classification via Invariant Learning
Fanlong Zeng, Wensheng Gan, Philip S. Yu +1
The class imbalance problem refers to the disproportionate distribution of samples across different classes within a dataset, where the minority classes are significantly underrepr…
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…
Utility-based Privacy Preserving Data Mining
Qingfeng Zhou, Wensheng Gan, Zhenlian Qi +1
With the advent of big data, periodic pattern mining has demonstrated significant value in real-world applications, including smart home systems, healthcare systems, and the medica…
Discovering Top-k Periodic and High-Utility Patterns
Qingfeng Zhou, Wensheng Gan, Guoting Chen
With a user-specified minimum utility threshold (minutil), periodic high-utility pattern mining (PHUPM) aims to identify high-utility patterns that occur periodically in a transact…
Targeted Mining of Time-Interval Related Patterns
Shuang Liang, Lili Chen, Wensheng Gan +2
Compared to frequent pattern mining, sequential pattern mining emphasizes the temporal aspect and finds broad applications across various fields. However, numerous studies treat te…
Graph Diffusion Network for Drug-Gene Prediction
Jiayang Wu, Wensheng Gan, Philip S. Yu
Predicting drug-gene associations is crucial for drug development and disease treatment. While graph neural networks (GNN) have shown effectiveness in this task, they face challeng…
AI-Generated Content in Landscape Architecture: A Survey
Yue Xing, Wensheng Gan, Qidi Chen +1
Landscape design is a complex process that requires designers to engage in intricate planning, analysis, and decision-making. This process involves the integration and reconstructi…
Towards More Accurate Full-Atom Antibody Co-Design
Jiayang Wu, Xingyi Zhang, Xiangyu Dong +5
Antibody co-design represents a critical frontier in drug development, where accurate prediction of both 1D sequence and 3D structure of complementarity-determining regions (CDRs)…
Mixture of Experts (MoE): A Big Data Perspective
Wensheng Gan, Zhenyao Ning, Zhenlian Qi +1
As the era of big data arrives, traditional artificial intelligence algorithms have difficulty processing the demands of massive and diverse data. Mixture of experts (MoE) has show…
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…
Graph Contrastive Learning on Multi-label Classification for Recommendations
Jiayang Wu, Wensheng Gan, Huashen Lu +1
In business analysis, providing effective recommendations is essential for enhancing company profits. The utilization of graph-based structures, such as bipartite graphs, has gaine…
SeqRFM: Fast RFM Analysis in Sequence Data
Yanxin Zheng, Wensheng Gan, Zefeng Chen +2
In recent years, data mining technologies have been well applied to many domains, including e-commerce. In customer relationship management (CRM), the RFM analysis model is one of…
Watermarking Techniques for Large Language Models: A Survey
Yuqing Liang, Jiancheng Xiao, Wensheng Gan +1
With the rapid advancement and extensive application of artificial intelligence technology, large language models (LLMs) are extensively used to enhance production, creativity, lea…
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…
Digital Fingerprinting on Multimedia: A Survey
Wendi Chen, Wensheng Gan, Philip S. Yu
The explosive growth of multimedia content in the digital economy era has brought challenges in content recognition, copyright protection, and data management. As an emerging conte…