Problem of cheating with neural networks in language learning

Bibliographic Details
Parent link:	Язык. Общество. Образование.— 2023.— С. 141-148
Main Author:	Зайда А. В.
Corporate Author:	Национальный исследовательский Томский политехнический университет Школа базовой инженерной подготовки Отделение иностранных языков
Other Authors:	Согуляк Я. А. (727), Аксёнова Н. В. Наталия Валерьевна
Summary:	This study explores the performance of commercially available large language models in common language learning tasks. Structure and working principles of neural networks were considered to hypothesize which tasks would perform better. Experiments were conducted to verify the assumptions. Several variants of task adaptations were compared in tests to discover the most resistant to cheating Текстовый файл
Language:	English
Published:	2023
Series:	Актуальные векторы исследований и подходы в современной лингвистике
Subjects:	электронный ресурс труды учёных ТПУ language learning cheating large language models task evaluation task adaptation
Online Access:	http://earchive.tpu.ru/handle/11683/77924
Format:	Electronic Book Chapter
KOHA link:	https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=671978

Internet