3 citations · 5 across the 5 of their papers we have counts for
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cs.SE2025★ 3 cited
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.SE2024★ 2 cited
Evaluation-Driven Development and Operations of LLM Agents: A Process Model and Reference Architecture
Boming Xia, Qinghua Lu, Liming Zhu +3
Large Language Models (LLMs) have enabled the emergence of LLM agents, systems capable of pursuing under-specified goals and adapting after deployment. Evaluating such agents is ch…