A supervised fine-tuning approach using inverted multi-resolution planning scaffolds from public-domain novels trains models to generate book-length stories with more human-like literary qualities than standard instruction-tuned LLMs.
InProceedings of the 2020 15 Conference on Empirical Methods in Natural Language Processing, pages 4274–4295, Online
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Towards Human-Level Book-Writing Capability
A supervised fine-tuning approach using inverted multi-resolution planning scaffolds from public-domain novels trains models to generate book-length stories with more human-like literary qualities than standard instruction-tuned LLMs.