Researchers have developed DataSTORM, a novel LLM-based agent system designed for in-depth research on large-scale structured databases and internet sources. Unlike previous methods focused on unstructured web data, DataSTORM employs principles of Exploratory Data Analysis and Data Storytelling to facilitate thesis generation, quantitative reasoning, and narrative development. Evaluations on the InsightBench dataset show DataSTORM achieving a new state-of-the-art, with a significant improvement in insight and summary recall. Furthermore, on a real-world dataset derived from ACLED, DataSTORM outperformed proprietary systems like ChatGPT Deep Research according to both automated metrics and human assessments. AI
IMPACT Enhances LLM capabilities for structured data analysis, potentially improving research and business intelligence applications.
RANK_REASON The cluster describes a research paper detailing a new system for LLM-based research on structured databases. [lever_c_demoted from research: ic=1 ai=1.0]
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