Summary of Ev2r: Evaluating Evidence Retrieval in Automated Fact-checking, by Mubashara Akhtar et al.
Ev2R: Evaluating Evidence Retrieval in Automated Fact-Checking
by Mubashara Akhtar, Michael Schlichtkrull, Andreas Vlachos
First submitted to arxiv on: 8 Nov 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI); Information Retrieval (cs.IR); Machine Learning (cs.LG)
GrooveSquid.com Paper Summaries
GrooveSquid.com’s goal is to make artificial intelligence research accessible by summarizing AI papers in simpler terms. Each summary below covers the same AI paper, written at different levels of difficulty. The medium difficulty and low difficulty versions are original summaries written by GrooveSquid.com, while the high difficulty version is the paper’s original abstract. Feel free to learn from the version that suits you best!
| 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 presents a novel approach to evaluating automated fact-checking (AFC) models called Ev2R. The authors argue that current methods are limited by their reliance on evaluation metrics developed for different purposes and constraints imposed by closed knowledge sources. They introduce three types of approaches for evidence evaluation: reference-based, proxy-reference, and reference-less. These approaches are evaluated through agreement with human ratings and adversarial tests, showing that prompt-based scorers leveraging LLMs and reference evidence outperform traditional methods. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Automated fact-checking is a way to help us figure out if what we read online is true or not. Right now, most systems do this by comparing what they find with information from a trusted source like Wikipedia. But this method has some problems. In this paper, scientists are trying to come up with new ways to check the facts. They’re using something called Ev2R, which is a system that looks at different types of evidence and tries to decide if it’s true or not. The authors tested their approach by comparing it to what humans think is true and found that some methods work better than others. |
Keywords
* Artificial intelligence * Prompt
