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November 9, 2025Open Access

PublicAgent: Multi-Agent Design Principles From an LLM-Based Open Data Analysis Framework

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Authors

SMSina MontazeriYFYunhe FengKSKewei Sha

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Overview

PublicAgent demonstrates enhanced dataset discovery and statistical analysis in data-driven workflows, suggesting practicality in evidence-based decision-making.

Key Points

  • Multi-agent framework improves analysis outcomes, enhancing dataset discovery experience and statistical methods used.
  • Evaluation of five models illustrated a consistent win rate of 97.5% across specialized agents, emphasizing their effectiveness.
  • Focused architecture allows for streamlined intent clarification and reporting processes, which reduces errors in workflows.
  • Implications point to the necessity of model-aware designs to optimize agent effectiveness and overall analysis quality.

Cite This Study

Montazeri et al. (2025) studied this question.

synapsesocial.com/papers/690fdcdaf60c54d04ea38075https://doi.org/10.48550/arxiv.2511.03023
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