2 citations · 2 across the 7 of their papers we have counts for
10 papers
State-Aware Generation of Deployable Websites from Visual Prototypes and Requirements
Ruwei Pan, Junlei Shen, Linhao Wu +7
Generating deployable websites from visual prototypes and textual requirements is increasingly feasible with multimodal models, yet keeping generated projects consistent with their…
Do Modifications Made by Coding Agents Make Subsequent Software Maintenance Harder?
Ruwei Pan, John Zhang, Linhao Wu +3
Coding agents increasingly maintain repositories over time, where each change becomes the starting point for subsequent tasks. Yet existing benchmarks either start tasks from devel…
InfoAgent: Traceable Generation and Repair of Evidence-Grounded Infographics
Yifan Li, Tong Li, Qi Zeng +6
Reliable infographic generation requires facts, symbols, and visual relations to remain consistent through rendering and revision. Correcting one element also requires tracking its…
Persistent Cross-Attempt State Optimization for Repository-Level Code Generation
Ruwei Pan, Jiangshuai Wang, Qisheng Zhang +6
Large language models (LLMs) have achieved substantial progress in repository-level code generation. However, solving the same repository-level task often requires multiple attempt…
Toward Executable Repository-Level Code Generation via Environment Alignment
Ruwei Pan, Junlei Shen, Linhao Wu +5
Large language models (LLMs) have achieved strong performance on code generation, but existing methods still struggle with repository-level code generation under executable validat…
Toward Functional and Non-Functional Evaluation of Application-Level Code Generation
Ruwei Pan, Yakun Zhang, Qingyuan Liang +4
Large language models (LLMs) have achieved strong performance on code generation. However, most prior evaluations focus on snippet-level outputs, such as function generation or rep…
AdaCoder: An Adaptive Planning and Multi-Agent Framework for Function-Level Code Generation
Yueheng Zhu, Chao Liu, Xuan He +4
Recently, researchers have proposed many multi-agent frameworks for function-level code generation, which aim to improve software development productivity by automatically generati…
MoT: Modularization-of-Thought Prompting for Effective Code Generation
Ruwei Pan, Hongyu Zhang
Large Language Models are transforming software development by automatically generating code. Current prompting techniques such as Chain-of-Thought (CoT) suggest tasks step by step…
AgentDroid: A Multi-Agent Framework for Detecting Fraudulent Android Applications
Ruwei Pan, Hongyu Zhang, Zhonghao Jiang +1
With the increasing prevalence of fraudulent Android applications such as fake and malicious applications, it is crucial to detect them with high accuracy and adaptability. We pres…
CodeCoR: An LLM-Based Self-Reflective Multi-Agent Framework for Code Generation
Ruwei Pan, Hongyu Zhang, Chao Liu
Code generation aims to produce code that fulfills requirements written in natural language automatically. Large Language Models (LLMs) like ChatGPT have demonstrated promising eff…