A survey-based taxonomy that splits reproducibility in AI/ML into eight rigor aspects (repeatability, reproducibility, replicability, adaptability, model selection, label/data quality, meta/incentive, maintainability) with estimated prevalence among 101 papers.
Title resolution pending
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.LG 1years
2024 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
What Do Machine Learning Researchers Mean by "Reproducible"?
A survey-based taxonomy that splits reproducibility in AI/ML into eight rigor aspects (repeatability, reproducibility, replicability, adaptability, model selection, label/data quality, meta/incentive, maintainability) with estimated prevalence among 101 papers.