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Data Mixture Design and Contamination Management
Data Mixture Design and Contamination Management A training program is a data program with a model attached. You can spend weeks debating architectures and still lose the run because your mixture was unstable, your holdout was contaminated, or your pipeline quietly oversampled the easiest sources. Data mixture design is where “what we want the model […]
Data Quality Gating: Dedupe, Provenance, Filters
Data Quality Gating: Dedupe, Provenance, Filters Data quality is not an abstract virtue. It is the difference between a model that generalizes and a model that memorizes, between a system that earns trust and one that quietly repeats contamination. “Quality gating” is the set of mechanisms that decide what enters a training corpus, what is […]
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Data Mixtures and Scaling Patterns
- Data Mixtures and Scaling Patterns: Concepts and Practical Patterns
- Data Mixtures and Scaling Patterns: Failure Modes and Reliability Checks
- Data Mixtures and Scaling Patterns: Metrics, Tradeoffs, and Implementation Notes
- Data Mixtures and Scaling Patterns: What Changes in Production
- Data Mixtures and Scaling Patterns: Common Mistakes and How to Avoid Them
- Data Mixtures and Scaling Patterns: A Field Guide for Builders
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