most citedA Layered Architecture for Developing and Enhancing Capabilities in Large Language Model-based Software Systems

2 citations · 2 across the 3 of their papers we have counts for

collaborators

6 papers

cs.SE2025

AgentArcEval: An Architecture Evaluation Method for Foundation Model based Agents

Qinghua Lu, Dehai Zhao, Yue Liu +6

The emergence of foundation models (FMs) has enabled the development of highly capable and autonomous agents, unlocking new application opportunities across a wide range of domains…

cs.SE2025

RAGOps: Operating and Managing Retrieval-Augmented Generation Pipelines

Xiwei Xu, Hans Weytjens, Dawen Zhang +3

Recent studies show that 60% of LLM-based compound systems in enterprise environments leverage some form of retrieval-augmented generation (RAG), which enhances the relevance and a…

cs.SE2025

SeeAction: Towards Reverse Engineering How-What-Where of HCI Actions from Screencasts for UI Automation

Dehai Zhao, Zhenchang Xing, Qinghua Lu +2

UI automation is a useful technique for UI testing, bug reproduction, and robotic process automation. Recording user actions with an application assists rapid development of UI aut…

cs.HC2025

FactFlow: Automatic Fact Sheet Generation and Customization from Tabular Dataset via AI Chain Design & Implementation

Minh Duc Vu, Jieshan Chen, Zhenchang Xing +3

With the proliferation of data across various domains, there is a critical demand for tools that enable non-experts to derive meaningful insights without deep data analysis skills.…

cs.SE2024

Architectural Patterns for Designing Quantum Artificial Intelligence Systems

Mykhailo Klymenko, Thong Hoang, Xiwei Xu +4

Utilising quantum computing technology to enhance artificial intelligence systems is expected to improve training and inference times, increase robustness against noise and adversa…

cs.SE20242 cited

A Layered Architecture for Developing and Enhancing Capabilities in Large Language Model-based Software Systems

Dawen Zhang, Xiwei Xu, Chen Wang +2

Significant efforts has been made to expand the use of Large Language Models (LLMs) beyond basic language tasks. While the generalizability and versatility of LLMs have enabled wid…