Tell Me Why: Explainable Public Health Fact-Checking with Large Language Models
M Zarharan, P Wullschleger, BB Kia… - arXiv preprint arXiv …, 2024 - arxiv.org
This paper presents a comprehensive analysis of explainable fact-checking through a series
of experiments, focusing on the ability of large language models to verify public health …
of experiments, focusing on the ability of large language models to verify public health …
[PDF][PDF] Proceedings of the 4th Workshop on Trustworthy Natural Language Processing (TrustNLP 2024)
Welcome to TrustNLP 2024, the fourth Workshop on Trustworthy Natural Language Processing.
Colocated with NAACL 2024, the workshop is scheduled for June 21, 2024. To facilitate …
Colocated with NAACL 2024, the workshop is scheduled for June 21, 2024. To facilitate …
[PDF][PDF] Improving explainable fact-checking via sentence-level factual reasoning
Most existing fact-checking systems are unable to explain their decisions by providing
relevant rationales (justifications) for their predictions. It highlights a lack of transparency that …
relevant rationales (justifications) for their predictions. It highlights a lack of transparency that …