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Implementing active learning in natural language generation tasks

Grant US12579375B2 Kind: B2 Mar 17, 2026

Assignee

International Business Machines Corporation

Inventors

Liat Ein-Dor, Yotam Perlitz, Michal Shmueli-Scheuer, Dafna Sheinwald, Ariel Gera

Abstract

Methods, systems, and computer program products for implementing active learning in NLG tasks are provided herein. A computer-implemented method includes generating multiple natural language annotations associated with multiple items of unlabeled data by processing the unlabeled data using at least one artificial intelligence model; determining at least one quality score attributed to at least a portion of the multiple generated natural language annotations based at least in part on at least one quality metric; selecting at least one of the multiple natural language annotations and at least one corresponding item of the multiple items of unlabeled data based at least in part on the at least one determined quality score; and performing one or more automated actions based at least in part on the at least one selected natural language annotation.

CPC Classifications

G06F 40/40 G06N 20/00

Filing Date

2023-10-10

Application No.

18378249

Claims

20