Jing-Feng He

SAMP: source-aware multi-prototype learning for machine-generated text detection

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 unimod...