1 citations · 2 across the 5 of their papers we have counts for
6 papers
Multilingual Multimodal Software Developer for Code Generation
Linzheng Chai, Jian Yang, Shukai Liu +12
The rapid advancement of Large Language Models (LLMs) has significantly improved code generation, yet most models remain text-only, neglecting crucial visual aids like diagrams and…
MdEval: Massively Multilingual Code Debugging
Shukai Liu, Linzheng Chai, Jian Yang +15
Code large language models (LLMs) have made significant progress in code debugging by directly generating the correct code based on the buggy code snippet. Programming benchmarks,…
In-Context Code-Text Learning for Bimodal Software Engineering
Xunzhu Tang, Liran Wang, Yonghui Liu +6
Bimodal software analysis initially appeared to be within reach with the advent of large language models. Unfortunately, the complex interplay of natural language text and code in…
Delving into Commit-Issue Correlation to Enhance Commit Message Generation Models
Liran Wang, Xunzhu Tang, Yichen He +4
Commit message generation (CMG) is a challenging task in automated software engineering that aims to generate natural language descriptions of code changes for commits. Previous me…
TANet: Thread-Aware Pretraining for Abstractive Conversational Summarization
Ze Yang, Liran Wang, Zhoujin Tian +2
Although pre-trained language models (PLMs) have achieved great success and become a milestone in NLP, abstractive conversational summarization remains a challenging but less studi…
StyleDGPT: Stylized Response Generation with Pre-trained Language Models
Ze Yang, Wei Wu, Can Xu +5
Generating responses following a desired style has great potentials to extend applications of open-domain dialogue systems, yet is refrained by lacking of parallel data for trainin…