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New LeakageBench benchmark highlights persistent PII risks in document images

By PulseAugur Editorial · [1 sources] ·

Researchers have introduced LeakageBench, a new benchmark designed to assess the risk of personally identifiable information (PII) leakage from document images. This benchmark focuses on document-level redaction, ensuring that sensitive data is completely removed from entire pages, not just individual instances. Evaluations using LeakageBench showed that while tools like Code Interpreter can improve the localization of PII when paired with models like GPT-5.5, significant leakage risks persist at the page level. AI

IMPACT Highlights the ongoing challenges in achieving complete PII redaction in document images, even with advanced AI tools.

RANK_REASON The cluster contains a research paper introducing a new benchmark for evaluating PII leakage in document images. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CL →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New LeakageBench benchmark highlights persistent PII risks in document images

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24 / 100
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The cluster contains a research paper introducing a new benchmark for evaluating PII leakage in document images. [lever_c_demoted from research: ic=1 ai=1.0]
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Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
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paper, safety
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High
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Breaking (< 6h)
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COVERAGE [1]

  1. arXiv cs.CL TIER_1 English(EN) · Vishnu Prasad Vijaya Kumar, Santhosh Venkatesh, Ivan P. Yamshchikov ·

    LeakageBench: Document-Level Leakage Risk for Redacting Personally Identifiable Information in Document Images

    arXiv:2609.02207v1 Announce Type: cross Abstract: Real-world personally identifiable information (PII) redaction often operates on document images---scans, screenshots, and PDF renderings---where OCR errors, layout structure, and visual noise determine whether sensitive informati…

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