公开(公告)号：US11960838B2

公开(公告)日：2024-04-16

申请号：US17120075

申请日：2020-12-11

Applicant: 42Maru Inc.

Inventor： Dong Hwan Kim ,  Han Su Kim ,  Woo Tae Jeong ,  Ki Bong Sung ,  Hyeon Dey Kim

IPC: G06F40/279 ,  G06F40/35 ,  G06N3/08

CPC classification number: G06F40/279 ,  G06F40/35 ,  G06N3/08

Abstract: The present invention relates to a method for reinforcing a multiple-choice QA model based on adversarial learning techniques, wherein incorrect answers are further generated based on a data set used in the process of training the multiple-choice QA model to enrich data which are learnable by the multiple-choice QA model. To achieve this object, the method includes step A of an incorrect answer generation model encoding a text based on natural language text and a question, generating a second incorrect answer based on the text and the question, and transmitting the second incorrect answer to an incorrect answer test model, step B of the incorrect answer test model encoding the text, the question, a first correct answer corresponding to the text and the question, a first incorrect answer and the second incorrect answer, and selecting a second correct answer based on results of the encoding, step C of the incorrect answer test model generating a feedback by determining whether the first correct answer is identical to the second correct answer, and step D of the incorrect answer generation model and the incorrect answer test model performing self-learning based on the feedback.