Towards Automated Code Reviews: Does Learning Code Structure Help? - Hong Yi Lin; Patanamon Thongtanunam (SANER, 2023)

Improving Automated Code Reviews: Learning from Experience. - Hong Yi Lin; Patanamon Thongtanunam; Christoph Treude; Wachiraphan Charoenwet 001 (MSR, 2024)

Leveraging Reviewer Experience in Code Review Comment Generation. - Hong Yi Lin; Patanamon Thongtanunam; Christoph Treude; Michael W. Godfrey; Chunhua Liu; Wachiraphan Charoenwet 001 (CoRR, 2024)

Improving Automated Code Reviews: Learning From Experience. - Hong Yi Lin; Patanamon Thongtanunam; Christoph Treude; Wachiraphan Charoeanwet 001 (Zenodo, 2024)

CodeReviewQA: The Code Review Comprehension Assessment for Large Language Models. - Hong Yi Lin; Chunhua Liu; Haoyu Gao; Patanamon Thongtanunam; Christoph Treude (ACL (Findings), 2025)

Should Code Models Learn Pedagogically? A Preliminary Evaluation of Curriculum Learning for Real-World Software Engineering Tasks. - Kyi Shin Khant; Hong Yi Lin; Patanamon Thongtanunam (MSR, 2025)

Too Noisy To Learn: Enhancing Data Quality for Code Review Comment Generation. - Chunhua Liu; Hong Yi Lin; Patanamon Thongtanunam (MSR, 2025)

AI Safety in the Eyes of the Downstream Developer: A First Look at Concerns, Practices, and Challenges. - Haoyu Gao; Mansooreh Zahedi; Wenxin Jiang; Hong Yi Lin; James Davis; Christoph Treude (CoRR, 2025)

Hallucinations in Code Change to Natural Language Generation: Prevalence and Evaluation of Detection Metrics. - Chunhua Liu; Hong Yi Lin; Patanamon Thongtanunam (CoRR, 2025)

Exploring the Potential of Large Language Models in Fine-Grained Review Comment Classification. - Linh Nguyen; Chunhua Liu; Hong Yi Lin; Patanamon Thongtanunam (CoRR, 2025)