UNH at CheckThat! 2025: Fine-tuning Vs Prompting in Claim Extraction
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arXiv
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| Main Authors: | , , , , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866911142990839808 |
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| author | Wilder, Joe Kadapala, Nikhil Xu, Benji Alsaadi, Mohammed Parsons, Aiden Rogers, Mitchell Agarwal, Palash Hassick, Adam Dietz, Laura |
| author_facet | Wilder, Joe Kadapala, Nikhil Xu, Benji Alsaadi, Mohammed Parsons, Aiden Rogers, Mitchell Agarwal, Palash Hassick, Adam Dietz, Laura |
| contents | We participate in CheckThat! Task 2 English and explore various methods of prompting and in-context learning, including few-shot prompting and fine-tuning with different LLM families, with the goal of extracting check-worthy claims from social media passages. Our best METEOR score is achieved by fine-tuning a FLAN-T5 model. However, we observe that higher-quality claims can sometimes be extracted using other methods, even when their METEOR scores are lower. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2509_06883 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | UNH at CheckThat! 2025: Fine-tuning Vs Prompting in Claim Extraction Wilder, Joe Kadapala, Nikhil Xu, Benji Alsaadi, Mohammed Parsons, Aiden Rogers, Mitchell Agarwal, Palash Hassick, Adam Dietz, Laura Computation and Language Artificial Intelligence Information Retrieval We participate in CheckThat! Task 2 English and explore various methods of prompting and in-context learning, including few-shot prompting and fine-tuning with different LLM families, with the goal of extracting check-worthy claims from social media passages. Our best METEOR score is achieved by fine-tuning a FLAN-T5 model. However, we observe that higher-quality claims can sometimes be extracted using other methods, even when their METEOR scores are lower. |
| title | UNH at CheckThat! 2025: Fine-tuning Vs Prompting in Claim Extraction |
| topic | Computation and Language Artificial Intelligence Information Retrieval |
| url | https://arxiv.org/abs/2509.06883 |