Analogical Deep Research

Analogical Deep Research: LLM agents for foresight via historical analogy retrieval

Researchers introduce Analogical Deep Research (ADR), a new task and benchmark (ADR-bench) for evaluating whether LLM agents can find and leverage structural historical analogies for foresight analysis. The paper identifies a core failure mode: agents match on surface features rather than causal mechanisms. The authors propose CANA (Causal Analogical Researcher), an agentic framework using structural decomposition and reflective feedback, achieving up to 10% improvement in analogy generation and outperforming state-of-the-art deep research agents on ADR-bench.