STORM
Under a context of abundance, a significant disparity exists between the vast amounts of accessible information and what an individual can realistically assimilate. While large language models (LLMs) exhibit impressive generation abilities, they do not directly address this issue and even worsen the situation due to more texts produced. This research project explores building a knowledge curation agent that can proactively research a topic, organize the information, and present the most pertinent insights in a reader-friendly way. Hopefully, STORM can provide a good starting point for knowledge discovery and liberate in-depth learning from the laborious search process.
