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9.2
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Aron Resty Ramillano
Ronastery
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We can't build more private AI if we can't measure privacy intelligence. That's why we're highlighting the Priv-IQ benchmark, a new, solution-oriented framework for evaluating LLMs on eight key privacy competencies, from visual privacy to knowledge of privacy law. The direct connection to our work is clear: the researchers relied on samples from the Ai4Privacy dataset to build out questions for Privacy Risk Assessment and Multilingual Entity Recognition. This is the power of open-source collaboration. We provide the data building blocks, and researchers construct powerful new evaluation tools on top of them. It's a win-win for the entire ecosystem when we can all benefit from transparent, data-driven benchmarks that help push for better, safer AI. Kudos to Sakib Shahriar and Rozita A. Dara for this important contribution. Read the paper to see the results: https://www.proquest.com/docview/3170854914?pq-origsite=gscholar&fromopenview=true&sourcetype=Scholarly%20Journals #OpenSource #DataPrivacy #LLM #Anonymization #AIsecurity #HuggingFace #Ai4Privacy #Worldslargestopensourceprivacymaskingdataset
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