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Benchmark Evaluation of the WordBinary AI-Text Detection Model on 9,000 AI-Generated Texts and 2,000 Pre-2015 Human Academic-Paper Samples

2026-08-04

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<title>Abstract</title> <p>The growing use of large language models has increased demand for systems capable of distinguishing AI-generated text from genuine human writing. Such systems must achieve high sensitivity to machine-generated content while maintaining a sufficiently low false-positive rate to protect human authors. This study evaluated the WordBinary AI-text detection model using 11,000 labelled text s...

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Literature Corpus work: 0259ed5d-8e74-5f2c-a2df-52679e35467f
DOI: 10.21203/rs.3.rs-10448398/v1

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Benchmark Evaluation of the WordBinary AI-Text Detection Model on 9,000 AI-Generated Texts and 2,000 Pre-2015 Human Academic-Paper SamplesDOI 10.21203/rs.3.rs-10448398/v1Read

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