BafCloud vs Catching Unicorns with GLTR

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GLTR is a forensic text analysis demo that highlights how predictable each word in a passage looks to a language model and colors the text so you can spot machine-written prose at a glance. Paste a sample into the live demo, and GLTR ranks every next-word prediction from GPT-2 117M, painting likely picks green or yellow and surprising human choices purple.

Unlike black-box AI detectors that return a single score, GLTR shows the forensic footprint word by word, plus histograms for top-k counts, probability ratios, and prediction entropy across the passage. That makes it useful for teaching how generative models stick to safe, high-probability wording while human writers reach for rarer terms that still fit the topic.

Researchers, journalists, and educators use GLTR to compare sample texts, explore model behavior, and sanity-check suspicious copy. The project is free, open source, and backed by an ACL 2019 demo paper from MIT-IBM Watson AI Lab and Harvard NLP, though the maintainers note it was built for GPT-2 era text and may struggle with newer models like ChatGPT.