.png){kind=icon}
.png){kind=icon}
Return
Discussion of “LAMBDA: Large Model Based Data Agent”
.png){kind=icon}
PRE
AI
DOI：10.1080/01621459.2025.2560377.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Large language models (LLMs) are making waves for efficient and reproducible data analysis. We congratulate the authors on developing an impressive LLM-based data analysis system (Sun et al. Citation2025) that makes statistical and machine learning tools more accessible for users across diverse backgrounds. LAMBDA offers a remarkable contribution to this space by well-designing a dual-agent and code-free architecture for interactive data analysis. In contrast to fully autonomous LLM agents, the open-source LAMBDA emphasizes flexibility, robustness, human intervention, and domain adaptability. It provides an excellent choice for exploratory analysis and model prototyping with both structured and unstructured data.
Keywords:
Large language models
Data analysis
Dual-agent architecture
Code-free system
Human intervention
Journal
J
IF:
3
Papers:
5.1K
Citations:
4.8W