Papers by Jaeseok Yoo

2 papers
ArchCode: Incorporating Software Requirements in Code Generation with Large Language Models (2024.acl-long)

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Challenge: Despite the critical role of software requirements, these criteria have not been studied actively in previous code generation works.
Approach: They propose a framework that leverages in-context learning to organize and extrapolate unexpressed requirements from textual descriptions.
Outcome: The proposed framework generates functional requirements from textual descriptions and extrapolates unexpressed requirements from them.
PERC: Plan-As-Query Example Retrieval for Underrepresented Code Generation (2025.coling-main)

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Challenge: Using large language models to generate code has shown significant promise, but selecting effective examples to improve generation quality remains a challenging task.
Approach: They propose a framework that utilizes algorithmic plans to identify and retrieve effective examples.
Outcome: The proposed framework outperforms the state-of-the-art RAG methods in code generation even when the source and target languages match or differ.

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