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)
Incoming Non-self Citations Over Time
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Authors
- 1. Reham Omar (Concordia University)
- 2. Omij Mangukiya (Concordia University)
- 3. Essam Mansour (Concordia University)
BibTeX Citation
@inproceedings{omar_sigmod25,
title = {{Dialogue Benchmark Generation from Knowledge Graphs with Cost-Effective Retrieval-Augmented LLMs}},
author = {Omar, Reham and Mangukiya, Omij and Mansour, Essam},
series = {{SIGMOD} '25},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3709681},
url = {https://dl.acm.org/doi/10.1145/3709681},
year = {2025}
}Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 10,437 | Chatty-KG: A Multi-Agent AI System for On-Demand Conversational Question Answering over Knowledge Graphs | 2026 | SIGMOD | 5.093636e-05 |
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Outgoing Citations (Sorted by Pagerank)
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 |
|---|---|---|---|---|
| 5,969 | Maestro: Automatic Generation of Comprehensive Benchmarks for Question Answering Over Knowledge Graphs | 2023 | SIGMOD | 6.0247307e-05 |
| 10,023 | A Universal Question-Answering Platform for Knowledge Graphs | 2023 | SIGMOD | 5.1757914e-05 |
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