GLTR
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About
GLTR (Giant Language Model Test Room) is an open-source, visually forensic tool developed by MIT-IBM Watson AI lab and HarvardNLP to detect text automatically generated by large language models like GPT-2. It analyzes input text by checking what GPT-2 would have predicted at each position, then overlays a color-coded mask based on the observed word's ranking within the model's predictions (green for top 10, yellow for top 100, red for top 1,000, purple for others). This visual footprint helps users identify patterns indicative of machine generation, such as an abundance of highly likely words. The tool also provides detailed insights like top 5 predicted words, probabilities on hover, and aggregated histograms showing word category distribution, probability ratios, and prediction entropy. GLTR aims to help non-experts distinguish human-written text from AI-generated text by revealing statistical anomalies. It has limitations in scale but serves as a proof of concept for text detection methods.
Platform
Task
Features
• supports pasting any text for analysis
• provides three aggregated histograms (word category, probability ratio, entropy distribution)
• displays top 5 predicted words and probabilities on hover
• color-coded text overlay (green, yellow, red, purple)
• analyzes word ranking prediction
• uses gpt-2 117m language model
• forensic analysis of text generation likelihood
• visually detect automatically generated text
FAQs
What is GLTR?
GLTR is a visually forensic tool that helps users detect text automatically generated by large language models. It inspects the visual footprint of such text.
How does GLTR detect generated text?
GLTR uses the GPT-2 117M model to predict words and then visually overlays the text with colors based on how likely each observed word was under the model.
What do the colors in GLTR mean?
Green indicates a word is in the top 10 most likely predictions, yellow in the top 100, red in the top 1,000, and purple for less likely words.
What analysis features does GLTR offer?
GLTR displays top 5 predicted words and probabilities on hover. It also provides three histograms showing word category distribution, probability ratios, and prediction entropies for the whole text.
What are GLTR's limitations?
GLTR's main limitation is its scale, only detecting individual cases, not large-scale abuse. It also requires advanced language knowledge and assumes a simple sampling scheme.
Pricing Plans
Free
Free Plan• Visually detect automatically generated text
• Forensic analysis of text generation likelihood
• Uses GPT-2 117M language model
• Analyzes word ranking prediction
• Color-coded text overlay
• Displays top 5 predicted words and probabilities on hover
• Provides three aggregated histograms
• Open-source and publicly deployed
Job Opportunities
There are currently no job postings for this AI tool.
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