Automatic Fact-checking in English and Telugu
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arXiv
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| Format: | Preprint |
| Veröffentlicht: |
2025
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| author | Chikkala, Ravi Kiran Anikina, Tatiana Skachkova, Natalia Vykopal, Ivan Agerri, Rodrigo van Genabith, Josef |
| author_facet | Chikkala, Ravi Kiran Anikina, Tatiana Skachkova, Natalia Vykopal, Ivan Agerri, Rodrigo van Genabith, Josef |
| contents | False information poses a significant global challenge, and manually verifying claims is a time-consuming and resource-intensive process. In this research paper, we experiment with different approaches to investigate the effectiveness of large language models (LLMs) in classifying factual claims by their veracity and generating justifications in English and Telugu. The key contributions of this work include the creation of a bilingual English-Telugu dataset and the benchmarking of different veracity classification approaches based on LLMs. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2509_26415 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Automatic Fact-checking in English and Telugu Chikkala, Ravi Kiran Anikina, Tatiana Skachkova, Natalia Vykopal, Ivan Agerri, Rodrigo van Genabith, Josef Computation and Language False information poses a significant global challenge, and manually verifying claims is a time-consuming and resource-intensive process. In this research paper, we experiment with different approaches to investigate the effectiveness of large language models (LLMs) in classifying factual claims by their veracity and generating justifications in English and Telugu. The key contributions of this work include the creation of a bilingual English-Telugu dataset and the benchmarking of different veracity classification approaches based on LLMs. |
| title | Automatic Fact-checking in English and Telugu |
| topic | Computation and Language |
| url | https://arxiv.org/abs/2509.26415 |