GLTR
Detect Automatically Generated Text

What is GLTR?

GLTR (Giant Language Model Test Room) is a tool developed to help users identify text that has been automatically generated by large language models. It provides a visual interface for analyzing the likelihood of text being machine-generated based on statistical analysis of word predictions.

By leveraging the GPT-2 117M language model, GLTR analyzes input text and highlights words based on their probability ranking. This allows for a visual inspection of the text's "footprint," revealing how likely each word was predicted by the model. This forensic approach aids in discerning between human-written and machine-generated content.

Features

  • Visual Footprint: Highlights words based on prediction probability (green for top 10, yellow for top 100, red for top 1,000, and purple for the rest).
  • Prediction Analysis: Shows the top 5 predicted words and their probabilities for each word in the text.
  • Histograms: Displays aggregated data on word categories, probability ratios, and prediction entropy.
  • Model Comparison: Analyzes text against the GPT-2 117M language model.
  • Example Analyses: Provides pre-loaded examples of both human-written and machine-generated text for comparison.

Use Cases

  • Detecting fake news articles.
  • Identifying automatically generated reviews or comments.
  • Analyzing the authenticity of online content.
  • Assisting researchers in studying language models.
  • Verifying the originality of written submissions.

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