Data Analysis Agents
Overview
Data analysis agents combine language-model planning with tools such as Python, SQL, statistical packages, APIs, and visualization software to investigate data and explain results. Common approaches include code-generating agents, specialized multi-agent workflows, and systems grounded in schemas, ontologies, or domain-specific skills. Work spans business intelligence, spreadsheets, scientific research, and clinical or financial analysis, with growing emphasis on sandboxed execution, verification, provenance, and human oversight. Agents can handle bounded tasks, but ambiguity, long-running state, cross-source evidence, and silent methodological errors remain major challenges, as do evaluations that measure trustworthy end-to-end results rather than plausible outputs alone.
Latest papers
106 papers24 papers in the last four weeks, up 26% on the four weeks before. 0.1% of all new papers.