Beijing Waterdrop Technology Group Co., Ltd.

Yinfeng Li

Lei Xu

Ting Huang

Peng Shen

Xiaobo Zhou

Mingxing Huang

Hailun Liu

Zhizhuo Wang

A method and a device for outputting insurance outbound conversation information based on a generative large language model are provided, aiming to solve the problem of low accuracy in the output of insurance outbound conversation information based on generative large language models, which relates to the technical field of data processing. The method includes: acquiring conversation information in outbound consultation on an insurance product; classifying the conversation information with a trained generative large language model to obtain a classification result of the conversation information, where the generative large language model is trained with a training sample set obtained by performing deduplication on crossing area in formulated conversation sample data; and determining the insurance outbound conversation information for the outbound consultation based on the classification result and outputting the insurance outbound conversation information.

Method and device for outputting insurance outbound conversation information based on generative large language model

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Beijing, China

Yinfeng Li