collaborators

6 papers

cs.HC2026

Looks Right, Works Right: A Project-Level Benchmark for Multi-Screen Mobile App Generation

Fan Wu, Cuiyun Gao, Yiming Huang +3

Recent multimodal large language models can convert visual designs directly into executable code, but real mobile products require multiple screenshots to become a buildable codeba…

cs.SE2026

Benchmarking Multimodal LLMs on Code Generation for Complex Interactive Webpages

Fan Wu, Lishuai Dong, Cuiyun Gao +4

Recent advancements in multimodal large language models (MLLMs) have achieved remarkable progress in multimodal reasoning and code generation, catalyzing a new paradigm for front-e…

cs.SE2026

LLM-Based Test Case Generation in DBMS through Monte Carlo Tree Search

Yujia Chen, Yingli Zhou, Fangyuan Zhang +1

Database Management Systems (DBMSs) are fundamental infrastructure for modern data-driven applications, where thorough testing with high-quality SQL test cases is essential for ens…

cs.SE2025

Automated Prompt Generation for Code Intelligence: An Empirical study and Experience in WeChat

Kexing Ji, Shiyun Fu, Cuiyun Gao +4

Large Code Models (LCMs) show potential in code intelligence, but their effectiveness is greatly influenced by prompt quality. Current prompt design is mostly manual, which is time…

cs.SE2025

Towards Mitigating API Hallucination in Code Generated by LLMs with Hierarchical Dependency Aware

Yujia Chen, Mingyu Chen, Cuiyun Gao +3

Application Programming Interfaces (APIs) are crucial in modern software development. Large Language Models (LLMs) assist in automated code generation but often struggle with API h…

cs.SE2025

Smaller but Better: Self-Paced Knowledge Distillation for Lightweight yet Effective LCMs

Yujia Chen, Yang Ye, Zhongqi Li +2

Large code models (LCMs) have remarkably advanced the field of code generation. Despite their impressive capabilities, they still face practical deployment issues, such as high inf…