{"version":1,"type":"story","url":"https://digestai.news/story/researchers-introduce-recopii-framework-for-pii-masking-datasets","json":"https://digestai.news/story/researchers-introduce-recopii-framework-for-pii-masking-datasets.json","markdown":"https://digestai.news/story/researchers-introduce-recopii-framework-for-pii-masking-datasets.md","slug":"researchers-introduce-recopii-framework-for-pii-masking-datasets","headline":"Researchers introduce ReCoPII framework for PII masking datasets","summary":"Researchers released ReCoPII, a framework for creating contextual PII masking datasets without relying on single-author assumptions. The method uses ontology-constrained entity relations, generates placeholder sentences, and derives MASK/KEEP labels programmatically. It was tested on Korean documents from six domains, producing ReCoPII-Ko, a corpus with relation, privacy, and annotation labels.\n\nFour annotators agreed with 88.42% of ReCoPII’s sampled KEEP labels, compared to 26.27% for SPY-style augmentation on the same sources. Fine-tuning a contextual masking system with a PII detector reduced over-masking to 5.04% while keeping leakage under 4.18%. The detector matched XLM-R-large performance on KDPII with fewer parameters.","keyPoints":["ReCoPII avoids single-author bias by modeling entity relations and generating synthetic data with placeholders","On Korean documents, it achieved 88.42% annotator agreement for KEEP labels vs 26.27% for SPY-style methods","Fine-tuned detector over-masks at most 5.04% while keeping leakage under 4.18% on human-verified records"],"whyItMatters":"ReCoPII offers a scalable, privacy-preserving way to train PII-masking systems without real-world data, improving accuracy over existing methods.","category":{"slug":"research","name":"Research","url":"https://digestai.news/category/research"},"entities":{"companies":[],"models":["XLM-R-large"],"people":[]},"firstPublishedAt":"2026-10-28T04:00:00Z","updatedAt":"2026-10-28T04:00:00Z","sourceCount":1,"hasPrimarySource":true,"sources":[{"outlet":"arXiv cs.CL","title":"ReCoPII: A Relation-Grounded Framework for Building Contextual PII Masking Datasets","url":"https://arxiv.org/abs/2610.35925","publishedAt":"2026-10-28T04:00:00Z","type":"primary","primary":true,"lead":true}],"sourceNotes":null,"discussions":[],"thread":null,"cite":{"text":"Digest AI, \"Researchers introduce ReCoPII framework for PII masking datasets\", 28 October 2026, https://digestai.news/story/researchers-introduce-recopii-framework-for-pii-masking-datasets","publisher":"Digest AI","title":"Researchers introduce ReCoPII framework for PII masking datasets","datePublished":"2026-10-28T04:00:00Z","url":"https://digestai.news/story/researchers-introduce-recopii-framework-for-pii-masking-datasets"},"generatedBy":"Written by Digest AI's editorial model from the linked sources; the sources are the record.","license":"Headlines, digests and key points are written by Digest AI and may be quoted with a link to the story page. Linked articles belong to their publishers. Terms: https://digestai.news/terms#reuse"}