Feb. 19, 2024, 5:48 a.m. | Zhaoye Fei, Yunfan Shao, Linyang Li, Zhiyuan Zeng, Hang Yan, Xipeng Qiu, Dahua Lin

cs.CL updates on arXiv.org arxiv.org

arXiv:2401.14624v2 Announce Type: replace
Abstract: Large language models have demonstrated remarkable potential in various tasks, however, there remains a significant scarcity of open-source models and data for specific domains. Previous works have primarily focused on manually specifying resources and collecting high-quality data on specific domains, which significantly consume time and effort. To address this limitation, we propose an efficient data collection method~\textit{Query of CC} based on large language models. This method bootstraps seed information through a large language model and …

abstract arxiv cs.cl data domain domains knowledge language language models large language large language models open-source models public quality quality data query resources scale tasks type

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