Summary of Can Chatgpt Detect Deepfakes? a Study Of Using Multimodal Large Language Models For Media Forensics, by Shan Jia et al.
Can ChatGPT Detect DeepFakes? A Study of Using Multimodal Large Language Models for Media Forensics
by Shan Jia, Reilin Lyu, Kangran Zhao, Yize Chen, Zhiyuan Yan, Yan Ju, Chuanbo Hu, Xin Li, Baoyuan Wu, Siwei Lyu
First submitted to arxiv on: 21 Mar 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Cryptography and Security (cs.CR)
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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 investigates the capabilities of multimodal large language models (LLMs) in detecting DeepFakes, AI-generated media content that has become a concern due to its potential use in spreading disinformation. The authors conduct qualitative and quantitative experiments to demonstrate how LLMs can be used for DeepFake detection through careful experimental design and prompt engineering, revealing the ability of these models to expose AI-generated images without requiring programming. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The paper explores whether large language models (LLMs) can help detect fake media content, like photos or videos. Researchers tested LLMs and found that they can identify when an image is computer-generated, which is important for stopping the spread of false information. This works because LLMs are good at understanding what makes something look real or fake. The study shows how to use these models for this task without needing special programming. |
Keywords
* Artificial intelligence * Prompt
