Multi-Agent Causal Discovery Using Large Language Models 事件

Multi-Agent Causal Discovery Using Large Language Models arXiv:2407.15073v4 Announce Type: replace-cross Abstract: Causal discovery aims to identify causal relationships between variables and is a fundamental problem across the sciences. Traditional statistical causal discovery (SCD) methods rely solely on observational data and ignore the contextual information available in metadata, whereas recent LLM-based methods exploit metadata but treat the large language model (LLM) as a single agent, l