52 citations · 58 across the 7 of their papers we have counts for
5 papers · 1 filter
Balancing Latency and Accuracy of Code Completion via Local-Cloud Model Cascading
Hanzhen Lu, Lishui Fan, Jiachi Chen +3
Line-level code completion requires a critical balance between high accuracy and low latency. Existing methods suffer from a trade-off: large language models (LLMs) provide high-qu…
ESALE: Enhancing Code-Summary Alignment Learning for Source Code Summarization
Chunrong Fang, Weisong Sun, Yuchen Chen +7
(Source) code summarization aims to automatically generate succinct natural language summaries for given code snippets. Such summaries play a significant role in promoting develope…
On the Effectiveness of Large Language Models in Domain-Specific Code Generation
Xiaodong Gu, Meng Chen, Yalan Lin +6
Large language models (LLMs) such as ChatGPT have shown remarkable capabilities in code generation. Despite significant achievements, they rely on enormous training data to acquire…
EALink: An Efficient and Accurate Pre-trained Framework for Issue-Commit Link Recovery
Chenyuan Zhang, Yanlin Wang, Zhao Wei +4
Issue-commit links, as a type of software traceability links, play a vital role in various software development and maintenance tasks. However, they are typically deficient, as dev…
RefBERT: A Two-Stage Pre-trained Framework for Automatic Rename Refactoring
Hao Liu, Yanlin Wang, Zhao Wei +4
Refactoring is an indispensable practice of improving the quality and maintainability of source code in software evolution. Rename refactoring is the most frequently performed refa…