LA-CPD: Local-Evidence-Aware Change-Point Detection for Human-LLM Authorship Segmentation
LA-CPD is proposed, a structured method that transforms noisy sentence-level score sequences into coherent authorship segments and outperforms WCP+AIC, increasing sentence-level accuracy from 0.747 to 0.796 while improving boundary localization and LLM-span delineation.
Qing Yang, Zhen-Yun Mao, Zi-Xiang Luo et al.
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