Demonstrating CEDAR: A System for Cost-Efficient Data-Driven Claim Verification
Summary: CEDAR maps claims to SQL for automated verification against relational data using LLMs. It dynamically orchestrates zero-shot, iterative/agent-based, and hybrid verification via cost-based optimization, with a demo and customizable datasets. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
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Authors
- 1. Tharushi Jayasekara (Cornell University)
- 2. Immanuel Trummer (Cornell University)
BibTeX Citation
@inproceedings{jayasekara_sigmod25,
title = {{Demonstrating CEDAR: A System for Cost-Efficient Data-Driven Claim Verification}},
author = {Jayasekara, Tharushi and Trummer, Immanuel},
series = {{SIGMOD} '25},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3722212.3725098},
url = {https://dl.acm.org/doi/10.1145/3722212.3725098},
year = {2025}
}Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 10,234 | CEDAR: A System for Cost-Efficient Data-Driven Claim Verification | 2025 | VLDB | 5.0432098e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 10 of 10 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 1 | Access Path Selection in a Relational Database Management System | 1979 | SIGMOD | 0.0023948467 |
| 430 | ATHENA: An Ontology-Driven System for Natural Language Querying over Relational Data Stores | 2016 | VLDB | 0.00018415668 |
| 523 | NaLIR: An Interactive Natural Language Interface for Querying Relational Databases | 2014 | SIGMOD | 0.0001689006 |
| 2,486 | ClaimBuster: The First-ever End-to-end Fact-checking System | 2017 | VLDB | 8.3800359e-05 |
| 3,183 | Toward Computational Fact-Checking | 2014 | VLDB | 7.5408249e-05 |
| 4,904 | Verifying Text Summaries of Relational Data Sets | 2019 | SIGMOD | 6.3477561e-05 |
| 5,694 | Mining an "Anti-Knowledge Base" from Wikipedia Updates with Applications to Fact Checking and Beyond | 2020 | VLDB | 6.0176005e-05 |
| 6,029 | Perturbation Analysis of Database Queries | 2016 | VLDB | 5.8912089e-05 |
| 7,779 | Buckle: Evaluating Fact Checking Algorithms Built on Knowledge Bases | 2019 | VLDB | 5.4377978e-05 |
| 7,780 | User Guidance for Efficient Fact Checking | 2019 | VLDB | 5.4377978e-05 |
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