{
  "id": 6096,
  "url": "https://arxiv.org/abs/2605.00845v1",
  "title": "Graph Query Generation with Constraint-guided Large Language Agents",
  "summary": "Knowledge Graph Question Answering (KGQA) has advanced through structured query generation, yet most efforts target RDF/SPARQL, leaving Cypher and property graphs underexplored, despite increasing demand for unified KGQA in industry settings. We propose UniQGen, a novel constraint-based framework that employs LLM agents to dynamically extract and refine representative graph query clauses into executable, intent-aligned graph queries across query languages. The foundation of our method is a varia",
  "authors": "Mengying Wang, Nicolaas Jedema, Rahul Pandey, RaviKiran Krishnan, Jens Lehmann, Yinghui Wu",
  "category": "research",
  "topics": "agents-autonomy",
  "orgs": null,
  "regions": null,
  "published_at": "2026-04-09T21:50:47.000Z",
  "fetched_at": "2026-07-14T16:32:15.635Z",
  "source_slug": "arxiv-ethics",
  "source_name": "arXiv",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/6096",
  "original_url": "https://arxiv.org/abs/2605.00845v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}