@inproceedings{
wang2024autosurvey,
title={AutoSurvey: Large Language Models Can Automatically Write Surveys},
author={Yidong Wang and Qi Guo and Wenjin Yao and Hongbo Zhang and Xin Zhang and Zhen Wu and Meishan Zhang and Xinyu Dai and Min zhang and Qingsong Wen and Wei Ye and Shikun Zhang and Yue Zhang},
booktitle={The Thirty-eighth Annual Conference on Neural Information Processing Systems},
year={2024},
url={https://openreview.net/forum?id=FExX8pMrdT}
}
This paper introduces AutoSurvey, a speedy and well-organized methodology for automating the creation of comprehensive literature surveys in rapidly evolving fields like artificial intelligence. Traditional survey paper creation faces challenges due to the vast volume and complexity of information, prompting the need for efficient survey methods. While large language models (LLMs) offer promise in automating this process, challenges such as context window limitations, parametric knowledge constraints, and the lack of evaluation benchmarks remain. AutoSurvey addresses these challenges through a systematic approach that involves initial retrieval and outline generation, subsection drafting by specialized LLMs, integration and refinement, and rigorous evaluation and iteration. Our contributions include a comprehensive solution to the survey problem, a reliable evaluation method, and experimental validation demonstrating AutoSurvey's effectiveness.
AutoSurvey: Large Language Models Can Automatically Write Surveys
Yidong Wang Qi Guo Wenjin Yao Hongbo Zhang Xin Zhang Zhen Wu Meishan Zhang Xinyu Dai Min zhang Qingsong Wen Wei Ye Shikun Zhang Yue Zhang