24 citations · 55 across the 9 of their papers we have counts for
9 papers
XSearch: Explainable Code Search via Concept-to-Code Alignment
Yiming Liu, Ruofan Liu, Yun Lin +7
Semantic code search has been widely adopted in both academia and industry. These approaches embed natural-language queries and code snippets into a shared embedding space and retr…
CodeV: Issue Resolving with Visual Data
Linhao Zhang, Daoguang Zan, Quanshun Yang +10
Large Language Models (LLMs) have advanced rapidly in recent years, with their applications in software engineering expanding to more complex repository-level tasks. GitHub issue r…
SWE-bench-java: A GitHub Issue Resolving Benchmark for Java
Daoguang Zan, Zhirong Huang, Ailun Yu +17
GitHub issue resolving is a critical task in software engineering, recently gaining significant attention in both industry and academia. Within this task, SWE-bench has been releas…
CodeR: Issue Resolving with Multi-Agent and Task Graphs
Dong Chen, Shaoxin Lin, Muhan Zeng +14
GitHub issue resolving recently has attracted significant attention from academia and industry. SWE-bench is proposed to measure the performance in resolving issues. In this paper,…
GraphCoder: Enhancing Repository-Level Code Completion via Code Context Graph-based Retrieval and Language Model
Wei Liu, Ailun Yu, Daoguang Zan +5
The performance of repository-level code completion depends upon the effective leverage of both general and repository-specific knowledge. Despite the impressive capability of code…
CodeS: Natural Language to Code Repository via Multi-Layer Sketch
Daoguang Zan, Ailun Yu, Wei Liu +11
The impressive performance of large language models (LLMs) on code-related tasks has shown the potential of fully automated software development. In light of this, we introduce a n…
Can Programming Languages Boost Each Other via Instruction Tuning?
Daoguang Zan, Ailun Yu, Bo Shen +8
When human programmers have mastered a programming language, it would be easier when they learn a new programming language. In this report, we focus on exploring whether programmin…
PanGu-Coder2: Boosting Large Language Models for Code with Ranking Feedback
Bo Shen, Jiaxin Zhang, Taihong Chen +9
Large Language Models for Code (Code LLM) are flourishing. New and powerful models are released on a weekly basis, demonstrating remarkable performance on the code generation task.…
PanGu-Coder: Program Synthesis with Function-Level Language Modeling
Fenia Christopoulou, Gerasimos Lampouras, Milan Gritta +19
We present PanGu-Coder, a pretrained decoder-only language model adopting the PanGu-Alpha architecture for text-to-code generation, i.e. the synthesis of programming language solut…