Discovering the systematic errors made by machine learning models

Discovering systematic errors with cross-modal embeddings In this blog post, we introduce Domino, a new approach for discovering systematic errors made by machine learning models. We also discuss a framework for quantitatively evaluating methods like Domino. Links: šŸ“„ Paper (ICLR 2022) šŸŒ Longer Walkthrough šŸ’» GitHub šŸ“˜ Docs šŸ“’ Google Colab Machine learning models that achieve high overall accuracy often make systematic errors on coherent slices of validation data. What is a slice? A slice is a set