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This paper introduces a dataset and training framework that transforms human-authored novels into multi-resolution planning scaffolds, enabling long-context language models to generate book-scale fiction with more human-like prose and narrative dynamics.
CoAuthorAI is a human-in-the-loop system that combines retrieval-augmented generation and hierarchical outlines to enable accurate, coherent scientific book writing, achieving 98% recall and 82% human satisfaction in evaluations.