11 citations · 28 across the 14 of their papers we have counts for
4 papers · 2 filters
Is Agentic Code Review Helpful? Mining Developers' Feedback to CodeRabbit Reviews in the Wild
Hong Yi Lin, Mingzhao Liang, Patanamon Thongtanunam +1
Agentic code review, where autonomous agents provide code review comments on pull requests, is increasingly integrated into development workflows, yet there is limited empirical ev…
Agentic Code Review in the Terminal: A Trajectory-Level Analysis of Behavior, Cost, and Human-Alignment
Wachiraphan Charoenwet, Kla Tantithamthavorn, Patanamon Thongtanunam +3
Agentic code review in terminal-based environments enables early feedback during local development before pull request creation. However, existing evaluations remain performance-ce…
From Registry to Repository: How AI Agent Skills Are Written, Adapted, and Maintained
Haoyu Gao, Jai Lal Lulla, Hong Yi Lin +3
AI coding agents increasingly rely on skills: structured context bundles, typically a SKILLmd file with a YAML header and Markdown body, loaded on demand for domain knowledge, w…
HalluJudge: A Reference-Free Hallucination Detection for Context Misalignment in Code Review Automation
Kla Tantithamthavorn, Hong Yi Lin, Patanamon Thongtanunam +3
Large Language models (LLMs) have shown strong capabilities in code review automation, such as review comment generation, yet they suffer from hallucinations -- where the generated…