Buckle: Evaluating Fact Checking Algorithms Built on Knowledge Bases
Summary: BUCKLE is an open-source benchmark for evaluating fact-checking algorithms on knowledge bases in a fair, controlled setting. It shows how training/test fact properties and reference data shape performance and compares approaches, including link-prediction methods. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Viet-Phi Huynh (EURECOM)
- 2. Paolo Papotti (EURECOM)
BibTeX Citation
@article{huynh_vldb19,
title = {{Buckle: Evaluating Fact Checking Algorithms Built on Knowledge Bases}},
author = {Huynh, Viet-Phi and Papotti, Paolo},
journal = {PVLDB},
series = {{VLDB} '19},
volume = {12},
number = {12},
pages = {1798--1801},
doi = {10.14778/3352063.3352069},
url = {https://doi.org/10.14778/3352063.3352069},
year = {2019}
}Incoming Citations (Sorted by Pagerank)
Showing 2 of 2 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 10,717 | Demonstrating CEDAR: A System for Cost-Efficient Data-Driven Claim Verification | 2025 | SIGMOD | 5.093636e-05 |
| 10,983 | CEDAR: A System for Cost-Efficient Data-Driven Claim Verification | 2025 | VLDB | 5.093636e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 0 of 0 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|
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