Summary of Convnlp: Image-based Ai Text Detection, by Suriya Prakash Jambunathan et al.
ConvNLP: Image-based AI Text Detection
by Suriya Prakash Jambunathan, Ashwath Shankarnarayan, Parijat Dube
First submitted to arxiv on: 9 Jul 2024
Categories
- Main: Machine Learning (cs.LG)
- Secondary: Computation and Language (cs.CL)
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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 research paper explores the potential of Generative-AI technologies like Large Language models (LLMs) to revolutionize education, but also highlights the ethical concerns surrounding their misuse. The authors note that students are increasingly relying on powerful LLMs like GPT-4 and Llama 2 to complete assignments, compromising academic integrity. To address this issue, the paper presents a novel approach for detecting LLM-generated AI-text using a visual representation of word embedding and a Convolutional Neural Network called ZigZag ResNet, along with a scheduler named ZigZag Scheduler. The model demonstrates strong generalization capabilities on datasets generated by six different state-of-the-art LLMs, achieving an average detection rate of 88.35%. This solution offers a computationally efficient and faster alternative to existing tools for AI-generated text detection, contributing to the fight against academic dishonesty. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Students are relying more and more on powerful language models like GPT-4 and Llama 2 to complete their assignments. While this technology can be very helpful, it also raises concerns about academic integrity. Some students might use these models to cheat or copy work from others. Researchers have been working on ways to detect when text is generated by a machine instead of a student. A new approach uses a special kind of computer program called a Convolutional Neural Network (CNN) and a scheduler to detect AI-generated text. This solution can help make sure students are doing their own work, which is an important part of learning. |
Keywords
» Artificial intelligence » Cnn » Embedding » Generalization » Gpt » Llama » Neural network » Resnet
