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SAMP: Source-Aware Multi-Prototype Learning for Machine-Generated Text Detection

2026-05-15

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<title>Abstract</title> <p>Machine-generated text detection is commonly formulated as a binary classification problem that separates human-written texts from machine-generated ones. In heterogeneous settings involving diverse generators, domains, languages, and adversarial perturbations, binary classes are often not structurally simple or unimodal. Human-written texts typically exhibit broad dispersion, while mac...

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Literature Corpus work: c42c3305-a202-575e-b9bb-b6bf9d6ec86c
DOI: 10.21203/rs.3.rs-9598516/v1

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