10 citations · 14 across the 5 of their papers we have counts for
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cs.CL2024★ 1 cited
aiXcoder-7B: A Lightweight and Effective Large Language Model for Code Processing
Siyuan Jiang, Jia Li, He Zong +11
Large Language Models (LLMs) have been widely used in code completion, and researchers are focusing on scaling up LLMs to improve their accuracy. However, larger LLMs have lower in…
cs.CL2024
DevEval: A Manually-Annotated Code Generation Benchmark Aligned with Real-World Code Repositories
Jia Li, Ge Li, Yunfei Zhao +15
How to evaluate the coding abilities of Large Language Models (LLMs) remains an open question. We find that existing benchmarks are poorly aligned with real-world code repositories…
cs.SE2024★ 3 cited
DevEval: Evaluating Code Generation in Practical Software Projects
Jia Li, Ge Li, Yunfei Zhao +14
How to evaluate Large Language Models (LLMs) in code generation is an open question. Many benchmarks have been proposed but are inconsistent with practical software projects, e.g.,…