15 citations · 16 across the 3 of their papers we have counts for
3 papers
cs.SE2026
Coding in a Bubble? Evaluating LLMs in Resolving Context Adaptation Bugs During Code Adaptation
Tanghaoran Zhang, Xinjun Mao, Shangwen Wang +8
Code adaptation is a fundamental but challenging task in software development, requiring developers to modify existing code for new contexts. A key challenge is to resolve Context…
cs.SE2024★ 15 cited
FT2Ra: A Fine-Tuning-Inspired Approach to Retrieval-Augmented Code Completion
Qi Guo, Xiaohong Li, Xiaofei Xie +6
The rise of code pre-trained models has significantly enhanced various coding tasks, such as code completion, and tools like GitHub Copilot. However, the substantial size of these…
cs.SE2023★ 1 cited
Domain Adaptive Code Completion via Language Models and Decoupled Domain Databases
Ze Tang, Jidong Ge, Shangqing Liu +4
Large Language Models (LLMs) have demonstrated remarkable performance in code completion. However, due to the lack of domain-specific knowledge, they may not be optimal in completi…