arXiv AI
DataWeave: Deploying Human-LLM Analytics for Exploratory Structured Data Analysis
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arXiv Computation and Language
Aug 28
DataSTORM: Deep Research on Large-Scale Databases using Exploratory Data Analysis and Data Storytelling
DataSTORM is an LLM‑based agentic system designed to conduct deep research over large‑scale structured databases and internet sources. It applies principles of Exploratory Data Analysis and Data Storytelling to frame research as a thesis‑driven analytical process, iteratively generating hypotheses, performing quantitative reasoning, and crafting coherent narratives. Evaluations on InsightBench and a new ACLED‑based dataset show that DataSTORM surpasses existing systems, achieving significant improvements in insight‑level recall and summary‑level scores.
arXiv AI
5d ago
Intent Graph: Navigating the Analytical Reasoning Space for Exploratory Data Analysis
The paper introduces DAG-EDA, a system that pairs an intent graph and a multi-layered knowledge graph to help analysts navigate exploratory data analysis. The intent graph, driven by a grammar of analytical intent, breaks down ambiguous natural-language questions into concrete analysis tasks while preserving alternative paths for branching and comparison. The knowledge graph externalizes domain knowledge from a large language model, linking concepts to dataset variables so analysts can inspect and challenge how their questions map to data, with results displayed as interactive dashboards.
arXiv AI
Jul 8
Data Analysis in the Wild: Benchmarking Large Language Models Against Real-World Data Complexities
arXiv:2607. 06482v1 Announce Type: cross Abstract: Current benchmarks for evaluating Large Language Models (LLMs) in data analysis often fail to reflect real-world settings.
arXiv AI
Aug 18
Walk Before You Run: The Importance of Data Exploration for Data Analysis Agents
arXiv:2608. 16045v1 Announce Type: cross Abstract: LLM-based data-analysis tools are increasingly used to help users analyze messy spreadsheets and workbooks, from answering questions over uploaded files to generating code, summaries, and visualizations.
arXiv Computation and Language
Sep 18
Data Journalist Agent: Transforming Data into Verifiable Multimodal Stories
The paper introduces Data Journalist Agent (Data2Story), a multi‑agent framework that orchestrates specialized roles into a single virtual newsroom to produce evidence‑grounded, multimodal news stories. It ensures every claim is traceable to data, code, or external references via an Inspector, and generates interactive visualizations such as maps and audio to match reader interests. Evaluations on 18 articles show competitive performance in angle coverage, rubric scores, and verifiability, while human writers still lead in editorial angle and creative design.
arXiv AI
Jul 21
Natural Language Access to Domain-Specific Metadata: A Reusable Framework for LLM Query Generation
arXiv:2607. 18029v1 Announce Type: cross Abstract: Researchers need to answer ad-hoc questions about the contents of domain-specific archives but often lack the expertise to write structured queries on the metadata.