5 citations · 8 across the 11 of their papers we have counts for
Showing 2024 · cs.SEShow all
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cs.SE2024★ 1 cited
Evaluating the Effectiveness and Efficiency of Demonstration Retrievers in RAG for Coding Tasks
Pengfei He, Shaowei Wang, Shaiful Chowdhury +1
Retrieval-Augmented Generation (RAG) enhances Large Language Models (LLMs) by integrating external knowledge bases, achieving state-of-the-art results in various coding tasks. The…
cs.SE2024★ 1 cited
A Comprehensive Framework for Evaluating API-oriented Code Generation in Large Language Models
Yixi Wu, Pengfei He, Zehao Wang +3
Large language models (LLMs) like GitHub Copilot and ChatGPT have emerged as powerful tools for code generation, significantly enhancing productivity and accelerating software deve…
cs.SE2024★ 5 cited
ZS4C: Zero-Shot Synthesis of Compilable Code for Incomplete Code Snippets using LLMs
Azmain Kabir, Shaowei Wang, Yuan Tian +3
Technical Q&A sites are valuable for software developers seeking knowledge, but the code snippets they provide are often uncompilable and incomplete due to unresolved types and mis…