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PrivacyMind is a framework for fine-tuning large language models to incorporate domain-specific knowledge while protecting personally identifiable information during inference. It combines techniques like instruction tuning with positive and negative examples, penalty-based loss, and corpus curation to balance privacy protection with model performance.
AI named PrivacyMind from November 2025 to December 2025.