Gltr

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. Key Features : 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. Use Cases : 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.