GLTR
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About
GLTR, developed by the MIT-IBM Watson AI lab and HarvardNLP, is a tool designed to analyze the visual footprint of automatically generated text, enabling users to inspect how likely a text has been generated by automated systems. It utilizes the GPT-2 language model to predict the likelihood of text generation by overlaying a colored mask over input text, highlighting words based on their likelihood of appearance and providing visual indications of whether the text is human-written. This tool is valuable in detecting text generated by algorithms, such as fake reviews or news articles, facilitating forensic analysis to combat misinformation.
Platform
Task
Features
• forensic analysis of text generation
• visualization of text likelihood with color coding
• utilizes the gpt-2 language model
• interactive text inspection
• supports user input for text analysis
FAQs
What is GLTR?
GLTR is a tool designed to detect automatically generated text.
How does GLTR work?
GLTR uses the GPT-2 model to analyze the likelihood of each word in the input text and visualizes this information for analysis.
Can GLTR detect all automatically generated text?
GLTR may not detect large-scale abuses of automatically generated text and works best for individual cases.
Is GLTR free to use?
Yes, GLTR is available for public use and free to access.
What are the limitations of GLTR?
GLTR's main limitations include its scale and the assumption of a simple sampling scheme. It also requires an understanding of language nuances.
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