Method and device for reinforcement of multiple choice QA model based on adversarial learning techniques
US11960838B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 11, 2020 |
| Grant date | Apr 16, 2024 |
| Priority date | — |
| Expiry date | Dec 11, 2040 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/094
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
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.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.