mlsanityData to 14 Oct 2026

Techniques for supercharging academic writing with generative AI

arXiv 2310.17143 ↗First posted 26 Oct 2023cs.CY cs.CLcited by 9

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Abstract (arXiv)

Academic writing is an indispensable yet laborious part of the research enterprise. This Perspective maps out principles and methods for using generative artificial intelligence (AI), specifically large language models (LLMs), to elevate the quality and efficiency of academic writing. We introduce a human-AI collaborative framework that delineates the rationale (why), process (how), and nature (what) of AI engagement in writing. The framework pinpoints both short-term and long-term reasons for engagement and their underlying mechanisms (e.g., cognitive offloading and imaginative stimulation). It reveals the role of AI throughout the writing process, conceptualized through a two-stage model for human-AI collaborative writing, and the nature of AI assistance in writing, represented through a model of writing-assistance types and levels. Building on this framework, we describe effective prompting techniques for incorporating AI into the writing routine (outlining, drafting, and editing) as well as strategies for maintaining rigorous scholarship, adhering to varied journal policies, and avoiding overreliance on AI. Ultimately, the prudent integration of AI into academic writing can ease the communication burden, empower authors, accelerate discovery, and promote diversity in science.

Key facts. Cited by 9 papers in the map (data through 14 Oct 2026). Builds on 0 of its 28 references that are in the map. First posted on arXiv 26 Oct 2023.

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Citing papers per year: 2023: 1; 2024: 3; 2025: 5.

9 papers.