LAMBDA: A Large Model Based Data Agent
Maojun Sun, Ruijian Han, Binyan Jiang, Houduo Qi, Defeng Sun, Yancheng Yuan, and Jian Huang

TL;DR
LAMBDA is an open-source, multi-agent system utilizing large language models to facilitate code-free, natural language-driven data analysis with human-AI collaboration and external model integration.
Contribution
It introduces a novel multi-agent framework with programmer and inspector roles, enabling flexible, robust, and accessible data analysis without coding.
Findings
Demonstrated strong performance on real-world data analysis tasks.
Effective integration of external models and algorithms.
Enhanced user interaction and debugging capabilities.
Abstract
We introduce LArge Model Based Data Agent (LAMBDA), a novel open-source, code-free multi-agent data analysis system that leverages the power of large language models. LAMBDA is designed to address data analysis challenges in data-driven applications through innovatively designed data agents using natural language. At the core of LAMBDA are two key agent roles: the programmer and the inspector, which are engineered to work together seamlessly. Specifically, the programmer generates code based on the user's instructions and domain-specific knowledge, while the inspector debugs the code when necessary. To ensure robustness and handle adverse scenarios, LAMBDA features a user interface that allows direct user intervention. Moreover, LAMBDA can flexibly integrate external models and algorithms through our proposed Knowledge Integration Mechanism, catering to the needs of customized data…
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Taxonomy
TopicsData Mining Algorithms and Applications · Data Stream Mining Techniques · Advanced Database Systems and Queries
