Summary of Llms in Political Science: Heralding a New Era Of Visual Analysis, by Yu Wang
LLMs in Political Science: Heralding a New Era of Visual Analysis
by Yu Wang
First submitted to arxiv on: 29 Feb 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- 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 The paper explores the feasibility of using large language models (LLMs) like Gemini for image content analysis in political science, particularly object detection. The authors analyze a corpus of 688 images, finding high accuracy with Gemini-based object detection. Additionally, they demonstrate how Gemini can be used for other tasks such as face identification, sentiment analysis, and caption generation. The paper highlights the potential benefits of using LLMs like Gemini to accelerate image research in political science and social sciences. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper uses a special kind of computer model called Gemini to help understand what’s happening in pictures. Researchers who study politics and society want to learn more about these images, but they need special training or equipment. Gemini makes it easy for anyone to use by asking just one question and getting fast results without needing any special machines. The authors tested Gemini on 688 images and found that it does a great job of recognizing objects in pictures. They also showed how Gemini can be used for other things like finding faces, understanding emotions, or writing captions. This could really help make image research faster and easier. |
Keywords
» Artificial intelligence » Gemini » Object detection
