| dc.contributor.author | Kupershtein, L. | en |
| dc.contributor.author | Zalepa, O. | en |
| dc.contributor.author | Sorokolit, V. | en |
| dc.contributor.author | Prokopenko, S. | en |
| dc.contributor.author | Куперштейн, Л. М. | uk |
| dc.date.accessioned | 2026-05-25T08:18:15Z | |
| dc.date.available | 2026-05-25T08:18:15Z | |
| dc.date.issued | 2025 | |
| dc.identifier.citation | Kupershtein L., Zalepa O., Sorokolit V., Prokopenko S. AI-agent-based system for fact-checking support using large language models // Proceedings of the 7th Workshop for Young Scientists in Computer Science & Software Engineering (CS&SE@SW 2024), Kryvyi Rih, Ukraine, December 27, 2024. Kryvyi Rih, 2024. P. 321–331. URІ: https://cssesw.easyscience.education/cssesw2024/CSSESW2024/paper50.pdf. | en |
| dc.identifier.issn | 1613-0073 | |
| dc.identifier.uri | https://ir.lib.vntu.edu.ua//handle/123456789/51674 | |
| dc.description.abstract | In today’s world, the problem of disinformation is becoming increasingly relevant due to the speed of information
dissemination and the influence of social media. This article examines the impact of fake news on society and its
political, economic and social consequences. Special attention is paid to the use of large language models (LLMs)
to automate the fact-checking process. Describes the capabilities of LLMs in verifying information, including text
analysis, comparison with reliable sources, and contextualization. At the same time, the risks of using LLMs to
create fake news are highlighted. Proposes an architecture of an AI-based disinformation detection tool, which
includes query processing modules, a database, work with web resources, and results analytics. This approach is
aimed at improving the efficiency and accuracy of information verification. | en |
| dc.language.iso | en_US | en_US |
| dc.publisher | CEUR-WS | en |
| dc.relation.ispartof | Proceedings of the 7th Workshop for Young Scientists in Computer Science & Software Engineering (CS&SE@SW 2024), Kryvyi Rih, Ukraine, December 27, 2024. Kryvyi Rih, 2024 : 321–331. | en |
| dc.relation.uri | https://cssesw.easyscience.education/cssesw2024/CSSESW2024/paper50.pdf | |
| dc.subject | fake news | en |
| dc.subject | disinformation | en |
| dc.subject | fact-checking | en |
| dc.subject | large language model | en |
| dc.subject | AI-agent | en |
| dc.subject | RAG | en |
| dc.title | AI-agent-based system for fact-checking support using large language models | en |
| dc.type | Article, Scopus-WoS | |
| dc.type | Article | |
| dc.identifier.orcid | https://orcid.org/0000-0003-4712-3916 | |
| dc.identifier.orcid | https://orcid.org/0009-0008-2847-2006 | |
| dc.identifier.orcid | https://orcid.org/0009-0001-9177-3054 | |
| dc.identifier.orcid | https://orcid.org/0000-0003-4712-3916 | |