Navigating the Path of Writing: Outline-guided Text Generation with Large Language Models
<|reference_start|>Navigating the Path of Writing: Outline-guided Text Generation with Large Language Models: Large Language Models (LLMs) have significantly impacted the writing process, enabling collaborative content creation and enhancing productivity. However, generating high-quality, user-aligned text remains challenging. In this paper, we propose Writing Path, a framework that uses explicit outlines to guide LLMs in generating goal-oriented, high-quality pieces of writing. Our approach draws inspiration from structured writing planning and reasoning paths, focusing on capturing and reflecting user intentions throughout the writing process. We construct a diverse dataset from unstructured blog posts to benchmark writing performance and introduce a comprehensive evaluation framework assessing the quality of outlines and generated texts. Our evaluations with GPT-3.5-turbo, GPT-4, and HyperCLOVA X demonstrate that the Writing Path approach significantly enhances text quality according to both LLMs and human evaluations. This study highlights the potential of integrating writing-specific techniques into LLMs to enhance their ability to meet the diverse writing needs of users.<|reference_end|>
@article{lee2024navigating,
    title={Navigating the Path of Writing: Outline-guided Text Generation with
  Large Language Models},
    author={Yukyung Lee, Soonwon Ka, Bokyung Son, Pilsung Kang, Jaewook Kang},
    journal={arXiv preprint arXiv:2404.13919},
    year={2024},
    archivePrefix={arXiv},
    eprint={2404.13919},
    primaryClass={cs.CL cs.AI cs.HC}
}