SemMT: A Semantic-based Testing Approach for Machine Translation Systems. - Jialun Cao; Meiziniu Li; Yeting Li; Ming Wen 001; Shing-Chi Cheung (CoRR, 2020)

Facilitating Continuous Text Messaging in Online Romantic Encounters by Expanded Keywords Enumeration. - Taewook Kim; Qingyu Guo; Hyeonjae Kim; Wenjie Yang 004; Meiziniu Li; Xiaojuan Ma (CSCW Companion, 2022)

DeepFD: Automated Fault Diagnosis and Localization for Deep Learning Programs. - Jialun Cao; Meiziniu Li; Xiao Chen; Ming Wen 001; Yongqiang Tian 001; Bo Wu 018; Shing-Chi Cheung (ICSE, 2022)

MEMO: Coverage-guided Model Generation For Deep Learning Library Testing. - Meiziniu Li; Jialun Cao; Yongqiang Tian 001; Tsz On Li; Ming Wen 001; Shing-Chi Cheung (CoRR, 2022)

SemMT: A Semantic-Based Testing Approach for Machine Translation Systems. - Jialun Cao; Meiziniu Li; Yeting Li; Ming Wen 001; Shing-Chi Cheung; Haiming Chen 001 (ACM Trans. Softw. Eng. Methodol., 2022)

COMET: Coverage-guided Model Generation For Deep Learning Library Testing. - Meiziniu Li; Jialun Cao; Yongqiang Tian 001; Tsz On Li; Ming Wen 001; Shing-Chi Cheung (ACM Trans. Softw. Eng. Methodol., 2023)

Can LLMs Implicitly Learn Numeric Parameter Constraints in Data Science APIs? - Yinlin Deng; Chunqiu Steven Xia; Zhezhen Cao; Meiziniu Li; Lingming Zhang 001 (NeurIPS, 2024)

DLLens: Testing Deep Learning Libraries via LLM-aided Synthesis. - Meiziniu Li; Dongze Li; Jianmeng Liu; Jialun Cao; Yongqiang Tian 001; Shing-Chi Cheung (CoRR, 2024)

From Informal to Formal - Incorporating and Evaluating LLMs on Natural Language Requirements to Verifiable Formal Proofs. - Jialun Cao; Yaojie Lu 001; Meiziniu Li; Haoyang Ma; Haokun Li; Mengda He; Cheng Wen 002; Le Sun 001; Hongyu Zhang 002; Shengchao Qin; Shing-Chi Cheung; Cong Tian (ACL (1), 2025)

A study on prompt design, advantages and limitations of ChatGPT for deep learning program repair. - Jialun Cao; Meiziniu Li; Ming Wen 001; Shing-Chi Cheung (Autom. Softw. Eng., 2025)