66 citations · 78 across the 9 of their papers we have counts for
9 papers
Structure-Aware RAG: Structured Retrieval Augmented Generation from Noisy Data for Conversational Agents
Kaiqiao Han, LuAn Tang, Renliang Sun +6
Large Language Models (LLMs) have been widely adopted in conversational applications. However, their reliance on parametric knowledge limits reliability in real-world scenarios tha…
Learning to Route: A Rule-Driven Agent Framework for Hybrid-Source Retrieval-Augmented Generation
Haoyue Bai, Haoyu Wang, Shengyu Chen +5
Large Language Models (LLMs) have shown remarkable performance on general Question Answering (QA), yet they often struggle in domain-specific scenarios where accurate and up-to-dat…
PAIL: Performance based Adversarial Imitation Learning Engine for Carbon Neutral Optimization
Yuyang Ye, Lu-An Tang, Haoyu Wang +5
Achieving carbon neutrality within industrial operations has become increasingly imperative for sustainable development. It is both a significant challenge and a key opportunity fo…
Heterogeneous Graph Matching Networks
Shen Wang, Zhengzhang Chen, Xiao Yu +7
Information systems have widely been the target of malware attacks. Traditional signature-based malicious program detection algorithms can only detect known malware and are prone t…
Attentional Heterogeneous Graph Neural Network: Application to Program Reidentification
Shen Wang, Zhengzhang Chen, Ding Li +6
Program or process is an integral part of almost every IT/OT system. Can we trust the identity/ID (e.g., executable name) of the program? To avoid detection, malware may disguise i…
Accelerating Dependency Graph Learning from Heterogeneous Categorical Event Streams via Knowledge Transfer
Chen Luo, Zhengzhang Chen, Lu-An Tang +2
Dependency graph, as a heterogeneous graph representing the intrinsic relationships between different pairs of system entities, is essential to many data analysis applications, suc…
Collaborative Alerts Ranking for Anomaly Detection
Ying Lin, Zhengzhang Chen, Cheng Cao +5
Given a large number of low-level heterogeneous categorical alerts from an anomaly detection system, how to characterize complex relationships between different alerts, filter out…
Entity Embedding-based Anomaly Detection for Heterogeneous Categorical Events
Ting Chen, Lu-An Tang, Yizhou Sun +2
Anomaly detection plays an important role in modern data-driven security applications, such as detecting suspicious access to a socket from a process. In many cases, such events ca…
GID: Graph-based Intrusion Detection on Massive Process Traces for Enterprise Security Systems
Boxiang Dong, Zhengzhang Chen, Hui Wang +5
Intrusion detection system (IDS) is an important part of enterprise security system architecture. In particular, anomaly-based IDS has been widely applied to detect abnormal proces…