Reproducibility Report for ACM SIGMOD 2024 Paper: 'Grafite: Taming Adversarial Queries with Optimal Range Filters'
We have successfully reproduced the evaluation results in the paper. We appreciate that the authors have prepared detailed documents and automation scripts for reproducibility. Our reproduced results show similar trends and relationships between the alternatives compared and support the scientific contributions and claims of the original paper.
Authors
- Kyoseung Koo (ORCID: https://orcid.org/0000-0002-2560-923X)
- Yin Lou (ORCID: https://orcid.org/0009-0004-8329-7192)
- Carlos Enrique Muñiz-Cuza (ORCID: https://orcid.org/0000-0003-4286-3448)
- Giorgio Vinciguerra (ORCID: https://orcid.org/0000-0003-0328-7791)
- Marco Costa (ORCID: https://orcid.org/0009-0002-8397-7580)
Institutions
- University of Pisa (IT)
- Seoul National University (KR)
- Technische Universität Berlin (DE)
Publication Details
- Published
- 2025-03-21
- DOI
- https://doi.org/10.1145/3687998.3717045
- Primary Topic
- Adversarial Robustness in Machine Learning
- Type
- article
- Field-Weighted Citation Impact
- 0.00