ASIRF proposes adapting sensitive-data redaction to context without retraining the model
A preprint describes a system that retrieves domain-specific definitions of sensitive information at inference time. Its initial results favor its detection recall over a reference classifier in most tested combinations, although the information available does not make it possible to assess all error types or its readiness for real-world use.
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