{
  "id": 10955,
  "url": "https://arxiv.org/abs/2607.13602v1",
  "title": "Analogical Deep Research: Retrieving and Integrating Historical Analogies for Foresight Analysis",
  "summary": "Systematic comparisons between current situations and structurally similar past events in the historical, i.e., historical analogies, is among the most powerful tools for foresight analysis. In this work, we present a new task called Analogical Deep Research (ADR) to Large Language Model (LLM) agents and construct the first ADR benchmark ADR-bench to study whether LLM agents are able to find and leverage historical analogies when doing foresight analysis. Our investigation reveals a key obstacle",
  "authors": "Yongqiang Chen, Guangyi Chen, Yuewen Sun, Kun Zhang",
  "category": "research",
  "topics": "agents-autonomy,finance-investment",
  "orgs": null,
  "regions": null,
  "published_at": "2026-07-15T08:49:00.000Z",
  "fetched_at": "2026-07-16T05:10:56.605Z",
  "source_slug": "arxiv-cslg",
  "source_name": "arXiv cs.LG",
  "source_homepage": "https://arxiv.org/list/cs.LG/recent",
  "ethics_ai_record_url": "https://ethics.ai/record/10955",
  "original_url": "https://arxiv.org/abs/2607.13602v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}