Summary of Correcting Misinformation on Social Media with a Large Language Model, by Xinyi Zhou et al.
Correcting misinformation on social media with a large language model
by Xinyi Zhou, Ashish Sharma, Amy X. Zhang, Tim Althoff
First submitted to arxiv on: 17 Mar 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI)
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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 A new approach to combating misinformation on social media is proposed in this paper, which utilizes large language models (LLMs) to identify and explain the inaccuracies of misleading content. The researchers highlight the limitations of manual correction methods, such as their inability to be timely and scalable, and argue that LLMs could accelerate misinformation correction if equipped with recent information and credibility evaluation capabilities. The proposed model, called MUSE, is an LLM augmented with access to up-to-date information and a credibility evaluation module. MUSE identifies and explains content inaccuracies with references, conducts multimodal retrieval, and interprets visual content to verify and correct multimodal content. The paper also proposes 13 dimensions of misinformation correction quality and evaluates the performance of MUSE against GPT-4 and human responses. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Misinformation on social media is a big problem! This paper talks about how we can use computers to help fix it. They show that current methods for correcting misinformation are not very good because they take too long or don’t work well enough. The researchers propose a new way to do this using special computer models called large language models (LLMs). These models can process lots of information quickly and accurately, but they need some help to make sure what they’re saying is true. The proposed model, MUSE, is an LLM that gets its information from the internet and checks how credible it is before presenting the facts. This helps to prevent misinformation from spreading online. |
Keywords
» Artificial intelligence » Gpt
