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arXiv · 2410.12377

HerO at AVeriTeC: The Herd of Open Large Language Models for Verifying Real-World Claims

Yejun Yoon·Jaeyoon Jung·Seunghyun Yoon·Kunwoo Park
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Abstract

To tackle the AVeriTeC shared task hosted by the FEVER-24, we introduce a system that only employs publicly available large language models (LLMs) for each step of automated fact-checking, dubbed the Herd of Open LLMs for verifying real-world claims (HerO). For evidence retrieval, a language model is used to enhance a query by generating hypothetical fact-checking documents. We prompt pretrained and fine-tuned LLMs for question generation and veracity prediction by crafting prompts with retrieved in-context samples. HerO achieved 2nd place on the leaderboard with the AVeriTeC score of 0.57, suggesting the potential of open LLMs for verifying real-world claims. For future research, we make our code publicly available at https://github.com/ssu-humane/HerO.

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Yejun Yoon, Jaeyoon Jung, Seunghyun Yoon, Kunwoo Park. 2024-10-16. HerO at AVeriTeC: The Herd of Open Large Language Models for Verifying Real-World Claims. https://arxiv.org/abs/2410.12377

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