Zero-Shot Learning and Key Points Are All You Need for Automated Fact-Checking

• URL: http://arxiv.org/abs/2408.08400v1
• Date: Thu, 15 Aug 2024 19:57:42 GMT
• Title: Zero-Shot Learning and Key Points Are All You Need for Automated Fact-Checking
• Authors: Mohammad Ghiasvand Mohammadkhani, Ali Ghiasvand Mohammadkhani, Hamid Beigy,
• Abstract summary: This work introduces a framework based on Zero-Shot Learning and Key Points (ZSL-KeP) for automated fact-checking. It performs well on the AVeriTeC shared task dataset by robustly improving the baseline and achieving 10th place.
• Score: 10.788661063801703
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Automated fact-checking is an important task because determining the accurate status of a proposed claim within the vast amount of information available online is a critical challenge. This challenge requires robust evaluation to prevent the spread of false information. Modern large language models (LLMs) have demonstrated high capability in performing a diverse range of Natural Language Processing (NLP) tasks. By utilizing proper prompting strategies, their versatility due to their understanding of large context sizes and zero-shot learning ability enables them to simulate human problem-solving intuition and move towards being an alternative to humans for solving problems. In this work, we introduce a straightforward framework based on Zero-Shot Learning and Key Points (ZSL-KeP) for automated fact-checking, which despite its simplicity, performed well on the AVeriTeC shared task dataset by robustly improving the baseline and achieving 10th place.

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