Generative Large Language Models in Automated Fact-Checking: A Survey
Fuente:
arXiv
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| Autores principales: | , , , |
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| Formato: | Preprint |
| Publicado: |
2024
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| Acceso en línea: | |
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| _version_ | 1866912094936367104 |
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| author | Vykopal, Ivan Pikuliak, Matúš Ostermann, Simon Šimko, Marián |
| author_facet | Vykopal, Ivan Pikuliak, Matúš Ostermann, Simon Šimko, Marián |
| contents | The dissemination of false information on online platforms presents a serious societal challenge. While manual fact-checking remains crucial, Large Language Models (LLMs) offer promising opportunities to support fact-checkers with their vast knowledge and advanced reasoning capabilities. This survey explores the application of generative LLMs in fact-checking, highlighting various approaches and techniques for prompting or fine-tuning these models. By providing an overview of existing methods and their limitations, the survey aims to enhance the understanding of how LLMs can be used in fact-checking and to facilitate further progress in their integration into the fact-checking process. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2407_02351 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Generative Large Language Models in Automated Fact-Checking: A Survey Vykopal, Ivan Pikuliak, Matúš Ostermann, Simon Šimko, Marián Computation and Language The dissemination of false information on online platforms presents a serious societal challenge. While manual fact-checking remains crucial, Large Language Models (LLMs) offer promising opportunities to support fact-checkers with their vast knowledge and advanced reasoning capabilities. This survey explores the application of generative LLMs in fact-checking, highlighting various approaches and techniques for prompting or fine-tuning these models. By providing an overview of existing methods and their limitations, the survey aims to enhance the understanding of how LLMs can be used in fact-checking and to facilitate further progress in their integration into the fact-checking process. |
| title | Generative Large Language Models in Automated Fact-Checking: A Survey |
| topic | Computation and Language |
| url | https://arxiv.org/abs/2407.02351 |