Training a Question Answering Network Using Relational Loss

Patent №

US 11,610,069

Granted

2023-03-21

Filed 2020

Owner

NAVER CORPORATION

Lab

AI components

6

ml · nlp · vision · kr · planning · hardware

Assignment

Recorded

Dataset

AIPD

2023_r1 edition

Application

16889920

There is disclosed a computer implemented method that includes accessing a dataset having (1) a first set of questions including at least one pair of relational questions that correspond respectively with a pair of binary answers and (2) a second set of questions including at least another pair of relational questions that correspond respectively with a binary answer and a scalar answer. A question answering network is used to compute both a relational loss for the at least one pair of relational questions, and a relational loss for the at least another pair of relational questions. Both the relational loss for the at least one pair of relational questions and the relational loss for the at least another pair of relational questions are optimized, and a neural network model is trained with the optimized relational losses.

Machine learningNatural languageVisionKnowledge representationPlanningAI hardwareG06F 40/30G06F 40/40G06F 16/3344G06N 3/04G06N 3/042G06N 3/044G06N 3/0442G06N 3/045+5 more

AI classification

Machine learning1.00
Natural language1.00
Planning1.00
AI hardware1.00
Knowledge representation0.98
Vision0.63
Speech0.34
Evolutionary computation0.17

Ownership

NAVER CORPORATION

assignment · 533790909

Assignors

GRAIL, QUENTIN, PEREZ, JULIEN

On an employer assignment, the assignors are typically the inventors.

From the same owner

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