5 papers
CroissantMiner: Automated Extraction and Validation of Croissant Metadata for ML Datasets
Berke Arda, Ahmetcan Yavuz, Paul Gerry +7
Croissant has emerged as a standard for machine-readable dataset metadata, yet populating its fields remains labor-intensive and requires careful reading of accompanying dataset do…
Traceable Trust for action-ready artificial intelligence in bioscience
Huayu Xin, Yizhi Cai, Mukilan Deivarajan Suresh +9
Artificial intelligence (AI) is becoming part of the working infrastructure of the biosciences. AI models can predict biomolecular structures, design proteins, rank variants, annot…
Croissant Tasks: A Metadata Format for Reproducible Machine Learning Evaluations
Omar Benjelloun, Leonardo Martins Bianco, Isabelle Guyon +8
Reproducibility is fundamental to the scientific method, yet remains a critical challenge in machine learning. Contributing factors include underspecified execution details and bri…
Croissant Baker: Metadata Generation for Discoverable, Governable, and Reusable ML Datasets
Rafi Al Attrach, Rajna Fani, Sebastian Lobentanzer +17
Croissant has emerged as the metadata standard for machine learning datasets, providing a structured, JSON-LD-based format that makes dataset discovery, automated ingestion, and re…
AI Benchmark Democratization and Carpentry
Gregor von Laszewski, Wesley Brewer, Jeyan Thiyagalingam +28
Benchmarks are a cornerstone of modern machine learning, enabling reproducibility, comparison, and scientific progress. However, AI benchmarks are increasingly complex, requiring d…