@inproceedings{lee-etal-2024-tree,
title = "Tree-of-Question: Structured Retrieval Framework for {K}orean Question Answering Systems",
author = "Lee, Dongyub and
Jeong, Younghun and
Kim, Hwa-Yeon and
Yu, Hongyeon and
Han, Seunghyun and
Whang, Taesun and
Cho, Seungwoo and
Lee, Chanhee and
Lee, Gunsu and
Kim, Youngbum",
editor = "Yang, Yi and
Davani, Aida and
Sil, Avi and
Kumar, Anoop",
booktitle = "Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 6: Industry Track)",
month = jun,
year = "2024",
address = "Mexico City, Mexico",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2024.naacl-industry.35",
doi = "10.18653/v1/2024.naacl-industry.35",
pages = "406--418",
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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%0 Conference Proceedings
%T Tree-of-Question: Structured Retrieval Framework for Korean Question Answering Systems
%A Lee, Dongyub
%A Jeong, Younghun
%A Kim, Hwa-Yeon
%A Yu, Hongyeon
%A Han, Seunghyun
%A Whang, Taesun
%A Cho, Seungwoo
%A Lee, Chanhee
%A Lee, Gunsu
%A Kim, Youngbum
%Y Yang, Yi
%Y Davani, Aida
%Y Sil, Avi
%Y Kumar, Anoop
%S Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 6: Industry Track)
%D 2024
%8 June
%I Association for Computational Linguistics
%C Mexico City, Mexico
%F lee-etal-2024-tree
%X 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.
%R 10.18653/v1/2024.naacl-industry.35
%U https://aclanthology.org/2024.naacl-industry.35
%U https://doi.org/10.18653/v1/2024.naacl-industry.35
%P 406-418
Markdown (Informal)
[Tree-of-Question: Structured Retrieval Framework for Korean Question Answering Systems](https://aclanthology.org/2024.naacl-industry.35) (Lee et al., NAACL 2024)
ACL
- Dongyub Lee, Younghun Jeong, Hwa-Yeon Kim, Hongyeon Yu, Seunghyun Han, Taesun Whang, Seungwoo Cho, Chanhee Lee, Gunsu Lee, and Youngbum Kim. 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 (Volume 6: Industry Track), pages 406–418, Mexico City, Mexico. Association for Computational Linguistics.