DW-Bench: Benchmarking LLMs on Data Warehouse Graph Topology Reasoning
On the map: LLM reasoning → Knowledge- and tool-augmented reasoning
Abstract (arXiv)
This paper introduces DW-Bench, a new benchmark that evaluates large language models (LLMs) on graph-topology reasoning over data warehouse schemas, explicitly integrating both foreign-key (FK) and data-lineage edges. The benchmark comprises 1,046 automatically generated, verifiably correct questions across five schemas. Experiments show that tool-augmented methods substantially outperform static approaches but plateau on hard compositional subtypes.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Placed in Knowledge- and tool-augmented reasoning, one of 17 directions in LLM reasoning. Builds on 5 of its 23 references that are in the map. First posted on arXiv 21 Apr 2026.
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5 of 23 references.
References · 5
- 2024Qwen2.5 Technical Reportcited by 4,942
- 2024From Local to Global: A Graph RAG Approach to Query-Focused Summarizationcited by 1,453
- 2023Gemini: A Family of Highly Capable Multimodal Modelscited by 872
- 2024DeepSeek-V3 Technical Reportcited by 811
- 2026LLM-FK: Multi-Agent LLM Reasoning for Foreign Key Detection in Large-Scale Complex Databasescited by 1
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- 2026Unified Multi-Dimensional Benchmark for Complex Graph Reasoning in Large Language Models
- 2025Rethinking and Benchmarking Large Language Models for Graph Reasoning
- 2026Evaluating LLMs on Large-Scale Graph Property Estimation via Random Walks
- 2025Can LLMs Reason Structurally? Benchmarking via the Lens of Data Structures
- 2024Are Large-Language Models Graph Algorithmic Reasoners?
- 2025Grounding LLM Reasoning with Knowledge Graphs
- 2026ClosureBench: A Constructive Benchmark for Compositional Graph Reasoning