29 citations · 110 across the 38 of their papers we have counts for
7 papers · 1 filter
StepFly: Agentic Troubleshooting Guide Automation for Incident Diagnosis
Jiayi Mao, Liqun Li, Yanjie Gao +9
Effective incident management in large-scale IT systems relies on troubleshooting guides (TSGs), but their manual execution is slow and error-prone. While recent advances in LLMs o…
API Agents vs. GUI Agents: Divergence and Convergence
Chaoyun Zhang, Shilin He, Liqun Li +5
Large language models (LLMs) have evolved beyond simple text generation to power software agents that directly translate natural language commands into tangible actions. While API-…
Large Language Model-Brained GUI Agents: A Survey
Chaoyun Zhang, Shilin He, Jiaxu Qian +10
GUIs have long been central to human-computer interaction, providing an intuitive and visually-driven way to access and interact with digital systems. The advent of LLMs, particula…
The Vision of Autonomic Computing: Can LLMs Make It a Reality?
Zhiyang Zhang, Fangkai Yang, Xiaoting Qin +6
The Vision of Autonomic Computing (ACV), proposed over two decades ago, envisions computing systems that self-manage akin to biological organisms, adapting seamlessly to changing e…
TaskWeaver: A Code-First Agent Framework
Bo Qiao, Liqun Li, Xu Zhang +16
Large Language Models (LLMs) have shown impressive abilities in natural language understanding and generation, leading to their widespread use in applications such as chatbots and…
Everything of Thoughts: Defying the Law of Penrose Triangle for Thought Generation
Ruomeng Ding, Chaoyun Zhang, Lu Wang +7
Recent advancements in Large Language Models (LLMs) have revolutionized decision-making by breaking down complex problems into more manageable language sequences referred to as "th…
Introspective Tips: Large Language Model for In-Context Decision Making
Liting Chen, Lu Wang, Hang Dong +9
The emergence of large language models (LLMs) has substantially influenced natural language processing, demonstrating exceptional results across various tasks. In this study, we em…