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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.
Large Language Models (LLMs) increasingly participate in writing by modifying or extending human drafts, causing machine involvement to vary in both form and extent. Yet most Machine-Generated Text (MGT) detectors are evaluated only on fully human-written versus fully AI-generated text. Because human--AI collaboration...
The Trajectory-guided Forget-Recover Network (TFR-Net) is proposed, which separates persistent target-related channels from transient hotspots and suppresses only the persistent ones, and achieves a more favorable trade-off between unlearning effectiveness and retained utility than representative baselines.
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