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…
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…
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…
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…
AdaCCD: Adaptive Semantic Contrasts Discovery Based Cross Lingual Adaptation for Code Clone Detection
Yangkai Du, Tengfei Ma, Lingfei Wu +2
Code Clone Detection, which aims to retrieve functionally similar programs from large code bases, has been attracting increasing attention. Modern software often involves a diverse…
CP-BCS: Binary Code Summarization Guided by Control Flow Graph and Pseudo Code
Tong Ye, Lingfei Wu, Tengfei Ma +5
Automatically generating function summaries for binaries is an extremely valuable but challenging task, since it involves translating the execution behavior and semantics of the lo…