"LAMBDA: A Large Model Based Data Agent," "The ICML 2023 Ranking Experiment,"

Music City Center 

This session highlights two advances at the nexus of machine learning and statistical methodology.

The first paper, "LAMBDA: A Large Model Based Data Agent," introduces a code‐free, multi‐agent framework for statistical data analysis powered by large language models. A "programmer" agent generates domain‐aware code, while an "inspector" agent debugs, and a Knowledge Integration Mechanism incorporates external algorithms. Demonstrated on real‐world datasets, LAMBDA blends human‐in‐the‐loop statistical reasoning with AI automation to democratize complex analyses. Together, these contributions illustrate how ML‐driven tools can enhance the rigor and efficiency of both peer review and statistical data workflows.