Abstract
We introduce Korean language-specific RAG-based QA systems, primarily through the innovative Tree-of-Question (ToQ) methodology and enhanced query generation techniques. We address the complex, multi-hop nature of real-world questions by effectively integrating advanced LLMs with nuanced query planning. Our comprehensive evaluations, including a newly created Korean multi-hop QA dataset, demonstrate our method's ability to elevate response validity and accuracy, especially in deeper levels of reasoning. This paper not only showcases significant progress in handling the intricacies of Korean linguistic structures but also sets a new standard in the development of context-aware and linguistically sophisticated QA systems.
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CITATION STYLE
Lee, D., Jeong, Y., Kim, H., Yu, H., Han, S., Whang, T., … Kim, Y. (2024). Tree-of-Question: Structured Retrieval Framework for Korean Question Answering Systems. In Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL 2024 (Vol. 6, pp. 406–418). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/2024.naacl-industry.35
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