most citedPanGu-Coder2: Boosting Large Language Models for Code with Ranking Feedback

13 citations · 20 across the 5 of their papers we have counts for

collaborators

5 papers

cs.SE20244 cited

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…

cs.CL20242 cited

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…

cs.CL20241 cited

Improving Natural Language Capability of Code Large Language Model

Wei Li, Daoguang Zan, Bei Guan +3

Code large language models (Code LLMs) have demonstrated remarkable performance in code generation. Nonetheless, most existing works focus on boosting code LLMs from the perspectiv…

cs.CL2023

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…

cs.CL202313 cited

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.…