Auto-Cypher: Improving LLMs on Cypher generation via LLM-supervised generation-verification framework (2025.naacl-short)
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| Challenge: | Graph databases like Neo4j are gaining popularity for handling complex, interconnected data, over traditional relational databases. |
| Approach: | They propose an automated pipeline to generate Cypher queries for Neo4j using LLM-As-Database-Filler, a novel strategy for ensuring Cyphere query correctness. |
| Outcome: | The proposed pipeline generates high quality Cypher data containing 29.8k instances across various domains and queries with varying complexities. |
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