The Quarterly Achievement Meeting of the Research Group of Collection, Collation and Research of Chinese Ancient Agricultural Books was held from September 19th to 20th. Meanwhile, a large language model of Qi Min ancient agricultural text was released at the meeting.

More than 30 experts, scholars, postgraduate students and doctoral students attended the meeting. They were from Chinese Academy of Agricultural Sciences, National Library of China, Hubei Provincial Library, Huazhong Agricultural University, Zhengzhou Normal University, Hubei Science and Technology Publishing House, Kashgar Publishing House, Wuhan University and other universities, research institutions, libraries and publishing houses.

The Quarterly Achievement Meeting of the Research Group of Collection, Collation and Research of Chinese Ancient Agricultural Books was held at the Chinese Academy of Agricultural Sciences on the afternoon of 19th.

Xin Dai, Deputy Director of the Institute of Agricultural Information, Chinese Academy of Agricultural Sciences, congratulated the research group on its outstanding achievements, and hoped that the research group would explore more knowledge and cultural value of ancient agricultural books and expand the influence of the research on ancient agricultural books.

Yunpeng Cui, head of the sub-topic III, Institute of Agricultural Information, Chinese Academy of Agricultural Sciences, and his research group made a report on the research results of the large language model of Qi Min ancient agricultural text and its application in the open sharing and knowledge service platform of ancient agricultural books resources.

Heads of other sub-topics and key members reported the research progress and phased results respectively as followings:

Ren Xia, Huazhong Agricultural University Library,

Ping Luo, Hubei Science and Technology Publishing House,

Ziyang Weng, School of Remote Sensing and Information Engineering, Wuhan University,

Pengyan Mo, School of Communication of Zhengzhou Normal University.

Dongrong Xie, Deputy Director of the Rare Books Library, National Library of China, and Kun Qin, Professor at the School of Remote Sensing Information Engineering of Wuhan University, commented on the research situation of each sub-topic and gave suggestions.

Ping Wu, Chief Scientist of the project of Collection, Collation and Research of Chinese Ancient Agricultural Books, presided over the meeting and made a conclusion. She pointed out that each sub-topic research group should further implement the research tasks and summarize the research characteristics according to the topic task statement, so as to provide comprehensive, systematic and accurate research results for the society.

The launch event of the large language model of Qi Min ancient agricultural text was held at the Chinese Academy of Agricultural Sciences on the morning of 20th.

VIPs attended the launch event and addressed were as the followings:

Ping Wu, Professor at our School,

Xiujuan Chai, Deputy Director of the Major Tasks Bureau, Chinese Academy of Agricultural Sciences,

Xin Dai, Deputy Director of the Institute of Agricultural Information, Chinese Academy of Agricultural Sciences.

Yunpeng Cui gave a detailed introduction to the core functions, technological innovation and application fields of the large language model of Qi Min ancient agricultural text. Experts and scholars expressed their views on the application and improvement of the large language model of Qi Min ancient agricultural text and discussed its future development.

The large language model of Qi Min ancient agricultural text is one of the scientific research achievements of the national social science fund's major project Collection, Collation and Research of Chinese Ancient Agricultural Books. This model is based on the text training of a large number of Chinese ancient agricultural books, and has strong natural language processing ability, which can provide accurate answers to agricultural issues such as ancient agricultural planting, livestock and poultry breeding, farmland’s water conservancy and meteorological divination. Tools such as automatic text processing and semantic retrieval based on this model can provide efficient analytical support for agricultural ancient books researchers to carry out ancient social and agricultural research.