Papers by Young Cheol Jung

1 papers
Subject-level Inference for Realistic Text Anonymization Evaluation (2026.acl-long)

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Challenge: Existing text anonymization evaluations assume only a single data subject, ignoring multi-subject scenarios.
Approach: They propose a benchmark that shifts the unit of evaluation from text spans to individuals . they show that subject-level inference protection drops as low as 33% when masked .
Outcome: The proposed benchmark reduces the amount of protection available when PII spans are masked.

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