Navigating the Path of Writing: Outline-guided Text Generation with Large Language Models
April 22, 2024 ยท Declared Dead ยท ๐ North American Chapter of the Association for Computational Linguistics
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Authors
Yukyung Lee, Soonwon Ka, Bokyung Son, Pilsung Kang, Jaewook Kang
arXiv ID
2404.13919
Category
cs.CL: Computation & Language
Cross-listed
cs.AI,
cs.HC
Citations
15
Venue
North American Chapter of the Association for Computational Linguistics
Last Checked
4 months ago
Abstract
Large Language Models (LLMs) have impacted the writing process, enhancing productivity by collaborating with humans in content creation platforms. However, generating high-quality, user-aligned text to satisfy real-world content creation needs remains challenging. We propose WritingPath, a framework that uses explicit outlines to guide LLMs in generating goal-oriented, high-quality text. Our approach draws inspiration from structured writing planning and reasoning paths, focusing on reflecting user intentions throughout the writing process. To validate our approach in real-world scenarios, 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 various LLMs demonstrate that the WritingPath approach significantly enhances text quality according to evaluations by both LLMs and professional writers.
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