This is a tool developed by Stanford University that can automatically generate comprehensive and structured long articles like Wikipedia from scratch.
It can search the internet for information, simulate expert and author dialogues to generate structured article outlines, and finally produce complete articles.
Additionally, it will polish the articles, improve sentences, structure, and ensure the fluency and accuracy of the content.
Workflow:
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Automation of pre-writing research: In the traditional process of writing long articles, pre-writing research (including topic research, information gathering, and outline creation) is a time-consuming and complex task. STORM automates this process by searching the internet to gather detailed information on specific topics. It helps authors efficiently collect and organize the necessary information, thereby improving writing efficiency.
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Integration of multiple perspectives: For any given topic, to delve deeper into the subject, STORM asks questions from multiple perspectives. Exploring and understanding information from different perspectives is key to producing comprehensive and in-depth articles.
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Dialogue simulation: The system simulates dialogue scenarios, such as interaction between an expert and a writer, to better understand information and generate more accurate follow-up questions.
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Generating structured article outlines: A clear, logical article outline is the foundation of high-quality writing. After collecting enough information, STORM organizes this information into a structured content outline to provide a framework for writing articles.
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Article generation and polishing: Based on the outline and collected data, the system can generate complete articles and optimize the content through subsequent polishing processes, such as removing redundant information, adding summary sections, etc.
Paper: https://arxiv.org/abs/2402.14207
GitHub: https://github.com/stanford-oval/storm
Online Experience: https://storm.genie.stanford.edu