mlsanityData to 13 Oct 2026

Model Card for OpenAI Privacy Filter

arXiv 2608.18274 ↗First posted 18 Aug 2026cs.CR cs.LGcited by 2

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Abstract (arXiv)

OpenAI Privacy Filter is a compact, bidirectional token-classification model for detecting and redacting personally identifiable information (PII) and secrets in unstructured text. The model is derived from an autoregressively pretrained checkpoint and converted into a bidirectional, banded-attention classifier that labels an input sequence in a single forward pass. A constrained Viterbi decoder produces coherent spans across eight privacy categories and exposes configurable operating points for precision-recall tradeoffs. Privacy Filter has 1.5 billion total parameters, 50 million active parameters per token, and a 128,000-token context window. It is designed for efficient local deployment and domain-specific fine-tuning. Privacy Filter is intended as a configurable data-minimization component within layered privacy workflows, not as an anonymization or compliance guarantee.

Key facts. Cited by 2 papers in the map (data through 13 Oct 2026). Builds on 0 of its 1 references that are in the map. First posted on arXiv 18 Aug 2026.

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