OverleafCopilot: Empowering Academic Writing in Overleaf with Large Language Models

Fuente: arXiv
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Main Authors: Wen, Haomin, Wei, Zhenjie, Lin, Yan, Wang, Jiyuan, Liang, Yuxuan, Wan, Huaiyu
Format: Preprint
Published: 2024
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author Wen, Haomin
Wei, Zhenjie
Lin, Yan
Wang, Jiyuan
Liang, Yuxuan
Wan, Huaiyu
author_facet Wen, Haomin
Wei, Zhenjie
Lin, Yan
Wang, Jiyuan
Liang, Yuxuan
Wan, Huaiyu
contents The rapid development of Large Language Models (LLMs) has facilitated a variety of applications from different domains. In this technical report, we explore the integration of LLMs and the popular academic writing tool, Overleaf, to enhance the efficiency and quality of academic writing. To achieve the above goal, there are three challenges: i) including seamless interaction between Overleaf and LLMs, ii) establishing reliable communication with the LLM provider, and iii) ensuring user privacy. To address these challenges, we present OverleafCopilot, the first-ever tool (i.e., a browser extension) that seamlessly integrates LLMs and Overleaf, enabling researchers to leverage the power of LLMs while writing papers. Specifically, we first propose an effective framework to bridge LLMs and Overleaf. Then, we developed PromptGenius, a website for researchers to easily find and share high-quality up-to-date prompts. Thirdly, we propose an agent command system to help researchers quickly build their customizable agents. OverleafCopilot (https://chromewebstore.google.com/detail/overleaf-copilot/eoadabdpninlhkkbhngoddfjianhlghb ) has been on the Chrome Extension Store, which now serves thousands of researchers. Additionally, the code of PromptGenius is released at https://github.com/wenhaomin/ChatGPT-PromptGenius. We believe our work has the potential to revolutionize academic writing practices, empowering researchers to produce higher-quality papers in less time.
format Preprint
id arxiv_https___arxiv_org_abs_2403_09733
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle OverleafCopilot: Empowering Academic Writing in Overleaf with Large Language Models
Wen, Haomin
Wei, Zhenjie
Lin, Yan
Wang, Jiyuan
Liang, Yuxuan
Wan, Huaiyu
Computation and Language
Artificial Intelligence
The rapid development of Large Language Models (LLMs) has facilitated a variety of applications from different domains. In this technical report, we explore the integration of LLMs and the popular academic writing tool, Overleaf, to enhance the efficiency and quality of academic writing. To achieve the above goal, there are three challenges: i) including seamless interaction between Overleaf and LLMs, ii) establishing reliable communication with the LLM provider, and iii) ensuring user privacy. To address these challenges, we present OverleafCopilot, the first-ever tool (i.e., a browser extension) that seamlessly integrates LLMs and Overleaf, enabling researchers to leverage the power of LLMs while writing papers. Specifically, we first propose an effective framework to bridge LLMs and Overleaf. Then, we developed PromptGenius, a website for researchers to easily find and share high-quality up-to-date prompts. Thirdly, we propose an agent command system to help researchers quickly build their customizable agents. OverleafCopilot (https://chromewebstore.google.com/detail/overleaf-copilot/eoadabdpninlhkkbhngoddfjianhlghb ) has been on the Chrome Extension Store, which now serves thousands of researchers. Additionally, the code of PromptGenius is released at https://github.com/wenhaomin/ChatGPT-PromptGenius. We believe our work has the potential to revolutionize academic writing practices, empowering researchers to produce higher-quality papers in less time.
title OverleafCopilot: Empowering Academic Writing in Overleaf with Large Language Models
topic Computation and Language
Artificial Intelligence
url https://arxiv.org/abs/2403.09733