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%0 Conference Proceedings
%T FINALE : Finance Domain Instruction-Tuning Dataset with High-Quality Rationales via Chain-of-Thought Prompting
%A Lee, Sangmin
%A Oh, Suzie
%A Park, Saeran
%A Son, Guijin
%A Kang, Pilsung
%Y Chen, Chung-Chi
%Y Ishigaki, Tatsuya
%Y Takamura, Hiroya
%Y Murai, Akihiko
%Y Nishino, Suzuko
%Y Huang, Hen-Hsen
%Y Chen, Hsin-Hsi
%S Proceedings of the Eighth Financial Technology and Natural Language Processing and the 1st Agent AI for Scenario Planning
%D 2024
%8 3 aug
%I -
%C Jeju, South Korea
%F lee-etal-2024-finale
%U https://aclanthology.org/2024.finnlp-2.9
%P 89-106

Markdown (Informal)

[FINALE : Finance Domain Instruction-Tuning Dataset with High-Quality Rationales via Chain-of-Thought Prompting](https://aclanthology.org/2024.finnlp-2.9) (Lee et al., FinNLP 2024)

• FINALE : Finance Domain Instruction-Tuning Dataset with High-Quality Rationales via Chain-of-Thought Prompting (Lee et al., FinNLP 2024)

ACL

• Sangmin Lee, Suzie Oh, Saeran Park, Guijin Son, and Pilsung Kang. 2024. FINALE : Finance Domain Instruction-Tuning Dataset with High-Quality Rationales via Chain-of-Thought Prompting. In Proceedings of the Eighth Financial Technology and Natural Language Processing and the 1st Agent AI for Scenario Planning, pages 89–106, Jeju, South Korea. -.