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STORM: Search web data based on Topic to generate papers with citations, long paper reports

General Introduction

STORM is a knowledge integration and article generation system developed by the Oval team at Stanford University. It focuses on generating exhaustive Wikipedia-like articles (systematic papers) from scratch. The system utilizes large-scale language models for topic research, prepares summaries and simulates expert conversations from actual Internet sources to support writers in asking questions to produce lengthy articles containing citations.

 


STORM: Searching Internet data based on Topics and generating long article reports with citations

 

STORM: Searching Internet Data Based on Topics to Generate Long Article Reports with Citations-1

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STORM: Searching Internet Data Based on Topics to Generate Long Article Reports with Citations-1

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STORM: Searching Internet data based on Topics and generating long article reports with citations

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Function List

Researching topics and integrating knowledge
Creating topic summaries
Simulated conversations based on Internet sources
Automated writing to generate Wikipedia-like articles
Follow-up on topic understanding and questions through expert dialog
Code available and explored at GitHub
Live demo available

 

 

Using Help

Check out the GitHub repository for installation and configuration steps
Running code for prewriting phase of topic research
Conducting the writing phase of article writing and refinement

 

STORM runs online

 

1. Select Topic
2. Outline generation
3. Searching the Internet for cited material
4. Generate long articles with citations step by step based on an outline and a dialog strategy that mimics Wikipedia's professional writers and editors.

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