59 citations · 142 across the 51 of their papers we have counts for
Showing 2024 · cs.SEShow all
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cs.SE2024★ 11 cited
A Survey on Evaluating Large Language Models in Code Generation Tasks
Liguo Chen, Qi Guo, Hongrui Jia +9
This paper provides a comprehensive review of the current methods and metrics used to evaluate the performance of Large Language Models (LLMs) in code generation tasks. With the ra…
cs.SE2024
CoderUJB: An Executable and Unified Java Benchmark for Practical Programming Scenarios
Zhengran Zeng, Yidong Wang, Rui Xie +2
In the evolving landscape of large language models (LLMs) tailored for software engineering, the need for benchmarks that accurately reflect real-world development scenarios is par…
cs.SE2024★ 2 cited
CodeShell Technical Report
Rui Xie, Zhengran Zeng, Zhuohao Yu +3
Code large language models mark a pivotal breakthrough in artificial intelligence. They are specifically crafted to understand and generate programming languages, significantly boo…