Dialogue Benchmark Generation from Knowledge Graphs with Cost-Effective Retrieval-Augmented LLMs
Summary: Chatty-Gen: multi-stage retrieval-augmented platform to build domain-specific dialogue benchmarks from knowledge graphs. It uses stage-wise validation and efficient KG retrieval to curb hallucinations and cut costly LLM usage, beating baselines. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Reham Omar
- 2. Omij Mangukiya
- 3. Essam Mansour
Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 10,148 | Chatty-KG: A Multi-Agent AI System for On-Demand Conversational Question Answering over Knowledge Graphs | 2026 | SIGMOD | 4.1945683e-05 |
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Showing 2 of 2 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 4,204 | Maestro: Automatic Generation of Comprehensive Benchmarks for Question Answering Over Knowledge Graphs | 2023 | SIGMOD | 6.3607478e-05 |
| 9,875 | A Universal Question-Answering Platform for Knowledge Graphs | 2023 | SIGMOD | 4.2667743e-05 |
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