@inproceedings{hyojeong-etal-2024-esg-classification,
title = "{ESG} Classification by Implicit Rule Learning via {GPT}-4",
author = "Hyojeong, Yun and
Chanyoung, Kim and
Hahm, Moonjeong and
Kim, Kyuri and
Son, Guijin",
editor = "Chen, Chung-Chi and
Liu, Xiaomo and
Hahn, Udo and
Nourbakhsh, Armineh and
Ma, Zhiqiang and
Smiley, Charese and
Hoste, Veronique and
Das, Sanjiv Ranjan and
Li, Manling and
Ghassemi, Mohammad and
Huang, Hen-Hsen and
Takamura, Hiroya and
Chen, Hsin-Hsi",
booktitle = "Proceedings of the Joint Workshop of the 7th Financial Technology and Natural Language Processing, the 5th Knowledge Discovery from Unstructured Data in Financial Services, and the 4th Workshop on Economics and Natural Language Processing @ LREC-COLING 2024",
month = may,
year = "2024",
address = "Torino, Italia",
publisher = "ELRA and ICCL",
url = "https://aclanthology.org/2024.finnlp-1.28",
pages = "261--268",
abstract = "In this work, we adopt multiple prompting, chain-of-thought reasoning, and in-context learning strategies to guide GPT-4 in solving ESG classification tasks. We rank second in the Korean subset for Shared Task ML-ESG-3 in Impact Type prediction. Furthermore, we adopt open models to explain their calibration and robustness to different prompting strategies. The longer general pre-training correlates with enhanced performance in financial downstream tasks.",
}
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%0 Conference Proceedings
%T ESG Classification by Implicit Rule Learning via GPT-4
%A Hyojeong, Yun
%A Chanyoung, Kim
%A Hahm, Moonjeong
%A Kim, Kyuri
%A Son, Guijin
%Y Chen, Chung-Chi
%Y Liu, Xiaomo
%Y Hahn, Udo
%Y Nourbakhsh, Armineh
%Y Ma, Zhiqiang
%Y Smiley, Charese
%Y Hoste, Veronique
%Y Das, Sanjiv Ranjan
%Y Li, Manling
%Y Ghassemi, Mohammad
%Y Huang, Hen-Hsen
%Y Takamura, Hiroya
%Y Chen, Hsin-Hsi
%S Proceedings of the Joint Workshop of the 7th Financial Technology and Natural Language Processing, the 5th Knowledge Discovery from Unstructured Data in Financial Services, and the 4th Workshop on Economics and Natural Language Processing @ LREC-COLING 2024
%D 2024
%8 May
%I ELRA and ICCL
%C Torino, Italia
%F hyojeong-etal-2024-esg-classification
%X In this work, we adopt multiple prompting, chain-of-thought reasoning, and in-context learning strategies to guide GPT-4 in solving ESG classification tasks. We rank second in the Korean subset for Shared Task ML-ESG-3 in Impact Type prediction. Furthermore, we adopt open models to explain their calibration and robustness to different prompting strategies. The longer general pre-training correlates with enhanced performance in financial downstream tasks.
%U https://aclanthology.org/2024.finnlp-1.28
%P 261-268
Markdown (Informal)
[ESG Classification by Implicit Rule Learning via GPT-4](https://aclanthology.org/2024.finnlp-1.28) (Hyojeong et al., FinNLP-WS 2024)
ACL
- Yun Hyojeong, Kim Chanyoung, Moonjeong Hahm, Kyuri Kim, and Guijin Son. 2024. ESG Classification by Implicit Rule Learning via GPT-4. In Proceedings of the Joint Workshop of the 7th Financial Technology and Natural Language Processing, the 5th Knowledge Discovery from Unstructured Data in Financial Services, and the 4th Workshop on Economics and Natural Language Processing @ LREC-COLING 2024, pages 261–268, Torino, Italia. ELRA and ICCL.