Fangkai Yang, Pu Zhao 0004, Zezhong Wang 0004, Lu Wang, Bo Qiao 0001, Jue Zhang, Mohit Garg, Qingwei Lin, Saravan Rajmohan, Dongmei Zhang. Empower Large Language Model to Perform Better on Industrial Domain-Specific Question Answering. In Mingxuan Wang, Imed Zitouni, editors, Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing: EMNLP 2023 - Industry Track, Singapore, December 6-10, 2023. pages 294-312, Association for Computational Linguistics, 2023. [doi]
@inproceedings{Yang00W0ZGLRZ23,
title = {Empower Large Language Model to Perform Better on Industrial Domain-Specific Question Answering},
author = {Fangkai Yang and Pu Zhao 0004 and Zezhong Wang 0004 and Lu Wang and Bo Qiao 0001 and Jue Zhang and Mohit Garg and Qingwei Lin and Saravan Rajmohan and Dongmei Zhang},
year = {2023},
url = {https://aclanthology.org/2023.emnlp-industry.29},
researchr = {https://researchr.org/publication/Yang00W0ZGLRZ23},
cites = {0},
citedby = {0},
pages = {294-312},
booktitle = {Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing: EMNLP 2023 - Industry Track, Singapore, December 6-10, 2023},
editor = {Mingxuan Wang and Imed Zitouni},
publisher = {Association for Computational Linguistics},
}