STORM's unique feature is its ability to automate the research process by generating relevant questions. It uses two strategies: Perspective-Guided Question Asking, where it discovers different perspectives from similar topics to guide the question-asking process, and Simulated Conversation, where it simulates a conversation between a Wikipedia writer and a topic expert to update its understanding of the topic and ask follow-up questions. The article also provides a guide to set up and run STORM locally, customize its configurations, and evaluate its performance.
Key takeaways:
- STORM is a Large Language Model system designed to assist in writing Wikipedia-like articles from scratch, using Internet-based research to collect references and generate an outline.
- The system works in two stages: a pre-writing stage where it conducts research and generates an outline, and a writing stage where it uses the outline and references to generate a full-length article with citations.
- STORM uses two strategies to improve the depth and breadth of the questions it asks during the research process: Perspective-Guided Question Asking and Simulated Conversation.
- The code for STORM is highly modular and is seen as an example of automated knowledge curation, with ongoing work to enhance its extensibility.