Papers by Seonho An

1 papers
PlanRAG: A Plan-then-Retrieval Augmented Generation for Generative Large Language Models as Decision Makers (2024.naacl-long)

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Challenge: Existing methods for decision making require complex data analysis.
Approach: They propose a method that generates the plan for decision making as the first step and retrieves the queries for data analysis as the second step.
Outcome: The proposed method outperforms the state-of-the-art iterative plan-then-retrieval augmented generation method by 15.8% and 7.4% respectively.

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