| Title: | Chain-of-thought reasoning in language models |
| Authors: | Nemykin, N. B. |
| Keywords: | материалы конференций;chains of reasoning;language models;artificial intelligence;cognitive processes;explanatory modeling |
| Issue Date: | 2026 |
| Publisher: | БГУИР |
| Citation: | Nemykin, N. B. Chain-of-thought reasoning in language models / N. B.Nemykin // Актуальные вопросы экономики и информационных технологий : сборник материалов докладов 62-й научной конференции аспирантов, магистрантов и студентов БГУИР, Минск, 13–17 апреля 2026 г. / Белорусский государственный университет информатики и радиоэлектроники. – Минск, 2026. – С. 771. |
| Abstract: | This work looks at whether chain-of-thought prompting actually helps language models think through multi-step logic problems, or if it just makes their mistakes look more convincing. The key takeaway is that while walking through the reasoning step-by-step does improve accuracy, the models are still prone to subtle logic slips and the explanations they generate do not always reflect how they really got to the answer. |
| URI: | https://libeldoc.bsuir.by/handle/123456789/65377 |
| Appears in Collections: | Актуальные вопросы экономики и информационных технологий : материалы 62-й научной конференции аспирантов, магистрантов и студентов (2026)
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