Using Large Language Models to Document Code: A First Quantitative and Qualitative Assessment

被引：0

作者：

Guelman, Ian ^{[1
]}

Leal, Arthur Gregório ^{[2
]}

Xavier, Laerte ^{[2
]}

Valente, Marco Tulio ^{[1
]}

机构：

[1] Federal University of Minas Gerais (UFMG), Minas Gerais, Belo Horizonte, Brazil

[2] Pontifical Catholic University of Minas Gerais (PUCMG), Minas Gerais, Belo Horizonte, Brazil

来源：

arXiv |

关键词：

D O I：

暂无

中图分类号：

学科分类号：

摘要：

Program processors - System program documentation

引用

共 11 条

[1] Can large language models generate geospatial code?
State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, China
不详
arXiv, 1600,
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Muennighoff, Niklas
Liu, Qian
Zebaze, Armel
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Zhuo, Terry Yue
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da Cruz, António Miguel Rosado
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[9] Analyzing Cascading Outbreak of GameStop Event: A Practical Approach Using Network Analysis and Large Language Models
Lin, Shengyuan
Wang, Keyi
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ICAIF 2024 - 5th ACM International Conference on AI in Finance, : 428 - 436
[10] A Novel Approach for Automated Program Repair using Round-Trip Translation with Large Language Models
Ruiz, Fernando Vallecillos
Grishina, Anastasiia
Hort, Max
Moonen, Leon
arXiv,

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