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Introduces ScreenLeak, a benchmark for measuring PII redaction in computer-use AI data, and presents two local models (v45_phase3 for text and rfdetr_v8 for images) achieving near-frontier performance at low latency.
This case study empirically investigates where anonymization should be applied in Retrieval-Augmented Generation (RAG) pipelines to balance privacy and utility, examining the impact of anonymization at different stages (dataset vs. generated answer) to inform privacy risk mitigation strategies.