Kuaiji: the First Chinese Accounting Large Language Model

Autor:	Luo, Jiayuan, Yang, Songhua, Qiu, Xiaoling, Chen, Panyu, Nai, Yufei, Zeng, Wenxuan, Zhang, Wentao, Jiang, Xinke
Rok vydání:	2024
Předmět:	Computer Science - Computation and Language Computer Science - Artificial Intelligence
Druh dokumentu:	Working Paper
Popis:	Large Language Models (LLMs) like ChatGPT and GPT-4 have demonstrated impressive proficiency in comprehending and generating natural language. However, they encounter difficulties when tasked with adapting to specialized domains such as accounting. To address this challenge, we introduce Kuaiji, a tailored Accounting Large Language Model. Kuaiji is meticulously fine-tuned using the Baichuan framework, which encompasses continuous pre-training and supervised fine-tuning processes. Supported by CAtAcctQA, a dataset containing large genuine accountant-client dialogues, Kuaiji exhibits exceptional accuracy and response speed. Our contributions encompass the creation of the first Chinese accounting dataset, the establishment of Kuaiji as a leading open-source Chinese accounting LLM, and the validation of its efficacy through real-world accounting scenarios. Comment: version 2.0
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2402.13866 Zobrazit plný text záznamu View this record from Arxiv