Problem of cheating with neural networks in language learning
| Parent link: | Язык. Общество. Образование.— 2023.— С. 141-148 |
|---|---|
| Tác giả chính: | |
| Tác giả của công ty: | |
| Tác giả khác: | , |
| Tóm tắt: | 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 |
| Ngôn ngữ: | Tiếng Anh |
| Được phát hành: |
2023
|
| Loạt: | Актуальные векторы исследований и подходы в современной лингвистике |
| Những chủ đề: | |
| Truy cập trực tuyến: | http://earchive.tpu.ru/handle/11683/77924 |
| Định dạng: | Điện tử Chương của sách |
| KOHA link: | https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=671978 |
| Tóm tắt: | 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 |
|---|