Summary of Automated Justification Production For Claim Veracity in Fact Checking: a Survey on Architectures and Approaches, by Islam Eldifrawi et al.
Automated Justification Production for Claim Veracity in Fact Checking: A Survey on Architectures and Approaches
by Islam Eldifrawi, Shengrui Wang, Amine Trabelsi
First submitted to arxiv on: 9 Jul 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI); Information Retrieval (cs.IR); Machine Learning (cs.LG)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper explores the rapidly growing field of Automated Fact-Checking (AFC), which verifies the accuracy of online claims. By analyzing metadata and language patterns, AFC aims to discern truth from misinformation. The study surveys recent methodologies in this area, proposing a comprehensive taxonomy and tracing the evolution of research in the landscape. Additionally, it compares different approaches and provides insights into future directions for improving fact-checking explainability. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Fact-checking is super important because there’s so much false information online! This paper looks at how computers can help figure out what’s true or not. It talks about a few ways people are trying to do this, like looking at the words used and where they came from. The goal is to make it clear when something is true or not. |
