most citedLLM4DS: Evaluating Large Language Models for Data Science Code Generation

1 citations · 2 across the 2 of their papers we have counts for

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cs.SE2025★ 1 cited

Automated Non-Functional Requirements Generation in Software Engineering with Large Language Models: A Comparative Study

Jomar Thomas Almonte, Santhosh Anitha Boominathan, Nathalia Nascimento

Neglecting non-functional requirements (NFRs) early in software development can lead to critical challenges. Despite their importance, NFRs are often overlooked or difficult to ide…

cs.SE2024★ 1 cited

LLM4DS: Evaluating Large Language Models for Data Science Code Generation

Nathalia Nascimento, Everton Guimaraes, Sai Sanjna Chintakunta +1

The adoption of Large Language Models (LLMs) for code generation in data science offers substantial potential for enhancing tasks such as data manipulation, statistical analysis, a…