AutoSurvey: Large Language Models Can Automatically Write Surveys
arxiv(2024)
Abstract
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.
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