GLTR is an advanced tool developed by the MIT-IBM Watson AI lab and HarvardNLP to detect automatically generated text through forensic analysis. It focuses on analyzing the output of the GPT-2 117M language model from OpenAI, providing insights into the likelihood of a text being artificially generated.
Forensic text analysis: Detect automatically generated text using forensic analysis techniques.
Visual indication: Highlight words based on their likelihood of being generated by the language model.
Histogram insights: Analyze histograms to gather evidence of text generation and probability distributions.
Detection of fake text: Identify computer-generated text, such as fake reviews, comments, or news articles.
Fake review detection: Identify computer-generated text in reviews to ensure authenticity.
Comment analysis: Analyze comments to determine if they are likely to be generated by a language model.
News article verification: Detect artificially generated news articles to prevent the spread of misinformation.
GLTR empowers users to analyze text and detect computer-generated content using forensic analysis techniques. With its visual indication and histogram insights, GLTR serves as a valuable tool in identifying fake text generated by large language models.