Tag: data-governance

3 articles

• LLM Pretraining Data Mixture in Production: Controlling Capability Bias with Mixture Manifest, Token Budget, and Domain Loss Feedback

  A systematic guide to engineering data mixtures for LLM pretraining: using immutable Mixture Manifests to freeze domain weights and corpus versions, Token Budgets for precise accounting, and proxy model search, domain loss feedback, starvation protection, and replay gates to continuously calibrate capability structure. Turn mixture ratios from probabilistic parameters into auditable, reproducible training contracts.

  07/29/2026 LLM Pretraining / Data Mixture / DoReMi / RegMix / Data Governance / Token Budget / Mixture Manifest

• LLM Prompt Data Privacy in Production: Managing Prompt Data with PII Redaction, Retention Policies, and Audit Boundaries

  A systematic breakdown of prompt data privacy governance in LLM applications, covering PII redaction, retention policies, audit logs, vendor boundaries, and a go-live checklist to turn privacy governance from a 'not used for training' promise into a runnable engineering system.

  07/03/2026 llm-privacy / pii-redaction / data-governance / prompt-security / production

• LLM Fine-Tuning Data Governance: Stabilizing Model Quality with Versioning, Deduplication, and Contamination Detection

  An engineering deep dive into governing LLM fine-tuning datasets as production assets. Covers data version tracking, multi-level deduplication, train/validation contamination detection, quality gates, and model release rollback for trustworthy, reproducible, and auditable management.

  07/03/2026 LLM Fine-Tuning / Data Governance / Data Versioning / MLOps / Production AI