6 papers
Domain-Specific Data Synthesis for LLMs via Minimal Sufficient Representation Learning
Tong Ye, Hang Yu, Tengfei Ma +6
Large Language Models have demonstrated remarkable progress in general-purpose capabilities and can achieve strong performance in specific domains through fine-tuning on domain-spe…
A Problem-Oriented Perspective and Anchor Verification for Code Optimization
Tong Ye, Tengfei Ma, Xuhong Zhang +3
Large Language Models (LLMs) have shown remarkable capabilities in solving various programming tasks, such as code generation. However, their potential for code optimization, parti…
ModiGen: A Large Language Model-Based Workflow for Multi-Task Modelica Code Generation
Jiahui Xiang, Tong Ye, Peiyu Liu +2
Modelica is a widely adopted language for simulating complex physical systems, yet effective model creation and optimization require substantial domain expertise. Although large la…
LLM4EFFI: Leveraging Large Language Models to Enhance Code Efficiency and Correctness
Tong Ye, Weigang Huang, Xuhong Zhang +4
Large Language Models (LLMs), particularly Code LLMs, have demonstrated impressive performance in code generation. Current research primarily focuses on the correctness of generate…
Uncovering LLM-Generated Code: A Zero-Shot Synthetic Code Detector via Code Rewriting
Tong Ye, Yangkai Du, Tengfei Ma +4
Large Language Models (LLMs) have demonstrated remarkable proficiency in generating code. However, the misuse of LLM-generated (synthetic) code has raised concerns in both educatio…
LuaTaint: A Static Analysis System for Web Configuration Interface Vulnerability of Internet of Things Devices
Jiahui Xiang, Lirong Fu, Tong Ye +4
The diversity of web configuration interfaces for IoT devices has exacerbated issues such as inadequate permission controls and insecure interfaces, resulting in various vulnerabil…