most citedEmpowering AIOps: Leveraging Large Language Models for IT Operations Management

2 citations · 3 across the 5 of their papers we have counts for

collaborators

5 papers

cs.SE2026

Towards Structured, State-Aware, and Execution-Grounded Reasoning for Software Engineering Agents

Tse-Hsun, Chen

Software Engineering (SE) agents have shown promising abilities in supporting various SE tasks. Current SE agents remain fundamentally reactive, making decisions mainly based on co…

cs.SE2026

SWE-Refactor: A Repository-Level Benchmark for Real-World LLM-Based Code Refactoring

Yisen Xu, Jinqiu Yang, Tse-Hsun +1

Large Language Models (LLMs) have recently attracted wide interest for tackling software engineering tasks. In contrast to code generation, refactoring demands precise, semantics-p…

cs.SE2025

Evaluating Software Process Models for Multi-Agent Class-Level Code Generation

Wasique Islam Shafin, Md Nakhla Rafi, Zhenhao Li +1

Modern software systems require code that is not only functional but also maintainable and well-structured. Although Large Language Models (LLMs) are increasingly used to automate…

cs.SE20251 cited

MANTRA: Enhancing Automated Method-Level Refactoring with Contextual RAG and Multi-Agent LLM Collaboration

Yisen Xu, Feng Lin, Jinqiu Yang +3

Maintaining and scaling software systems relies heavily on effective code refactoring, yet this process remains labor-intensive, requiring developers to carefully analyze existing…

cs.SE20252 cited

Empowering AIOps: Leveraging Large Language Models for IT Operations Management

Arthur Vitui, Tse-Hsun Chen

The integration of Artificial Intelligence (AI) into IT Operations Management (ITOM), commonly referred to as AIOps, offers substantial potential for automating workflows, enhancin…