公开(公告)号：US20240143940A1

公开(公告)日：2024-05-02

申请号：US18544209

申请日：2023-12-18

Applicant: 42Maru Inc. ,  Korea Advanced Institute of Science and Technology

Inventor： Dong Hwan KIM ,  Sung Ju HWANG ,  Seanie LEE ,  Dong Bok LEE ,  Woo Tae JEONG ,  Han Su KIM ,  You Kyung KWON ,  Hyun Ok KIM

IPC: G06F40/35 ,  G06N3/045 ,  G06N3/08 ,  G06N5/04

CPC classification number: G06F40/35 ,  G06N3/045 ,  G06N3/08 ,  G06N5/04

Abstract: The present invention relates to a context-based QA generation architecture, and an object of the present invention is to generate diverse QA pairs from a single context. To achieve the object, the present invention includes a latent variable generating network including at least one encoder and an artificial neural network (Multi-Layer Perceptron: MLP) and configured to train the artificial neural network using a first context, a first question, and a first answer, and generate a second question latent variable and a second answer latent variable by applying the trained artificial neural network to a second context, an answer generating network configured to generate a second answer by decoding the second answer latent variable, and a question generating network configured to generate a second question based on a second context and the second answer.

公开(公告)号：US20210166102A1

公开(公告)日：2021-06-03

申请号：US16699443

申请日：2019-11-29

Applicant: 42Maru Inc.

Inventor： Dong Hwan KIM ,  Woo Tae JEONG ,  Seanie LEE ,  Gilje SEONG

IPC: G06N3/00 ,  G06N20/00

Abstract: A method of generating a question-answer learning model through adversarial learning may include: sampling a latent variable based on constraints in an input passage; generating an answer based on the latent variable; generating a question based on the answer; and machine-learning the question-answer learning model using a dataset of the generated question and answer, wherein the constraints are controlled so that the latent variable is present in a data manifold while increasing a loss of the question-answer learning model.

公开(公告)号：US20240232531A1

公开(公告)日：2024-07-11

申请号：US18611235

申请日：2024-03-20

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.

公开(公告)号：US20220179893A1

公开(公告)日：2022-06-09

申请号：US17125991

申请日：2020-12-17

Applicant: 42Maru Inc.

Inventor： Dong Hwan KIM ,  Han Su KIM ,  Woo Tae JEONG ,  Seung Hyeon LEE ,  Chang Hyeon LIM

IPC: G06F16/34 ,  G06F40/279 ,  G06F40/30 ,  G06F40/40 ,  G06F16/33 ,  G06F16/901

Abstract: The invention relates to a method and a system for improving performance of text summarization and has an object of improving performance of a technique for generating a summary from a given paragraph. According to the invention to achieve the object, a method for improving performance of text summarization includes: an a step of generating an embedding vector by vectorizing a natural language-based context; a b step of generating a graph by using the embedding vector; a c step of assigning a weight depending on whether or not a keyword corresponding to at least one node included in the graph is present in the context; and a d step of selecting a path having a highest likelihood in the graph and generating a summary based on the path.

公开(公告)号：US20220180061A1

公开(公告)日：2022-06-09

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 ,  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.

公开(公告)号：US20230342620A1

公开(公告)日：2023-10-26

申请号：US18214301

申请日：2023-06-26

Applicant: 42Maru Inc.

Inventor： Dong Hwan KIM ,  Woo Tae JEONG ,  Seanie LEE ,  Gilje SEONG

IPC: G06N3/088 ,  G06N20/00 ,  G06N3/004 ,  G06F16/33 ,  G06N3/08 ,  G06N3/045

CPC classification number: G06N3/088 ,  G06N20/00 ,  G06N3/004 ,  G06F16/3334 ,  G06F16/3346 ,  G06N3/08 ,  G06F16/3347 ,  G06N3/045

Abstract: A method of generating a question-answer learning model through adversarial learning may include: sampling a latent variable based on constraints in an input passage; generating an answer based on the latent variable; generating a question based on the answer; and machine-learning the question-answer learning model using a dataset of the generated question and answer, wherein the constraints are controlled so that the latent variable is present in a data manifold while increasing a loss of the question-answer learning model.

公开(公告)号：US20250021590A1

公开(公告)日：2025-01-16

申请号：US18898839

申请日：2024-09-27

Applicant: 42Maru Inc.

Inventor： Dong Hwan KIM ,  Han Su KIM ,  Woo Tae JEONG ,  Seung Hyeon LEE ,  Chang Hyeon LIM

IPC: G06F16/34 ,  G06F16/33 ,  G06F16/901 ,  G06F40/279 ,  G06F40/30 ,  G06F40/40

Abstract: The invention relates to a method and a system for improving performance of text summarization and has an object of improving performance of a technique for generating a summary from a given paragraph. According to the invention to achieve the object, a method for improving performance of text summarization includes: calculating a first likelihood of each of a plurality of nodes included in a graph corresponding to a natural language-based context; calculating a second likelihood of each of the plurality of nodes by assigning a weight to a first likelihood of a node corresponding to a keyword not presenting in the context among a plurality of keywords corresponding to each of the plurality of nodes; calculating a third likelihood of each of all paths present in the graph based on the second likelihood of each of the plurality of nodes; and generating a summary for the context based on a path having the highest third likelihood among the paths.