Radar Tester
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About
RADAR is an advanced AI-text detection tool designed to tackle the challenges posed by large language models (LLMs) in differentiating between AI-generated and human-generated texts. With the rise of ChatGPT-like applications, the fine line between machine-generated content and human writing has become increasingly blurred, leading to issues such as fake content, plagiarism, and wrongful accusations. Current AI-text detectors struggle against LLM-generated paraphrasing; however, RADAR addresses this issue with a novel approach that leverages adversarial learning. The framework consists of a paraphraser and a detector that continuously improve one another's effectiveness. Various experiments involving eight different LLMs demonstrated RADAR's superior performance compared to existing detection methods, especially in paraphrased content scenarios. Additionally, the tool shows strong adaptability and improved capabilities when evaluated with instruction-tuned LLMs.
Platform
Task
Features
• adversarial learning framework
• improved detection capabilities
• cross-dataset performance
• evaluated on multiple llms
• robust against llm paraphrasing
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