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.