DataPerf: Benchmarks for Data-Centric AI Development
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Valuable features might in many cases be as important as dataset size.
“Valuable features might in many cases be as important as dataset size229, which is a frequently discussed topic in the data-centric AI community230.”
From The METRIC-framework for assessing data quality for trustworthy AI in medicine: A systematic review (2024) · cites this paper as [229]
Cited by
Sorted by citations
The METRIC-framework for assessing data quality for trustworthy AI in medicine: A systematic review
Schwabe, D., Becker, K., Seyferth, M., Klaß, A., & Schaeffter, T. (2024) · npj Digital Medicine · doi:10.1038/s41746-024-01196-4 · Cited by 169 · see citing works
Hagendorff, T., Dasgupta, I., Binz, M., Chan, S. C. Y., Lampinen, A., Wang, J. X., Akata, Z., & Schulz, E. (2023) · arXiv · doi:10.48550/arxiv.2303.13988 · Cited by 68 · see citing works
- Authors
- Mazumder, M., Banbury, C., Yao, X., Karlaš, B., Rojas, W. G., Diamos, S., Diamos, G., He, L., Parrish, A., Kirk, H. R., Quaye, J., Rastogi, C., Kiela, D., Jurado, D., Kanter, D., Mosquera, R., Cukierski, W., Ciro, J., Aroyo, L., Acun, B., Chen, L., Raje, M., Bartolo, M., Eyuboglu, E. S., Ghorbani, A., Goodman, E., Howard, A., Inel, O., Kane, T., Kirkpatrick, C. R., Sculley, D., Kuo, T.-S., Mueller, J., Thrush, T., Vanschoren, J., Warren, M., Williams, A., Yeung, S., Ardalani, N., Paritosh, P., Zhang, C., Zou, J., Wu, C.-J., Coleman, C., Ng, A., Mattson, P., & Reddi, V. J.
- ORCID
- Mazumder, Mark
- Yao, Xiaozhe
- Karlaš, Bojan
- Parrish, Alicia
- Kirk, Hannah Rose
- Quaye, Jessica
- Rastogi, Charvi
- Mosquera, Rafael
- Ciro, Juan
- Aroyo, Lora
- Acun, Bilge
- Chen, Lingjiao
- Bartolo, Max
- Ghorbani, Amirata
- Goodman, Emmett
- Inel, Oana
- Kuo, Tzu-Sheng
- Mueller, Jonas
- Vanschoren, Joaquin
- Williams, Adina
- Yeung, Serena
- Ardalani, Newsha
- Zhang, Ce
- Zou, James
- Ng, Andrew
- Mattson, Peter
- Reddi, Vijay Janapa
- Venue
- Advances in Neural Information Processing Systems 36
- Published
- 2023
- Pages
- 5320-5347
- ISSN
- 1049-5258 (ISSN-L)
- OpenAlex
- W7133254352
- Cited by
- 5
- References
- 0
- Citations by year
- 2026: 5
- FWCI
- 1.43
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- neural information processing systems (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Networks and Communications › Advanced Database Systems and Queries
- Social Sciences › Decision Sciences › Information Systems and Management › Scientific Computing and Data Management
- Physical Sciences › Computer Science › Hardware and Architecture › Parallel Computing and Optimization Techniques
- Keywords
- benchmarking, data-centric AI, data quality, data preparation, data engineering, data pipelines, performance evaluation
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
