Daniel M. Jimenez-Gutierrez
2 indexed papers
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226
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AI×2Distributed×2ML×2NLP×1Crypto×1
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Research Timeline
2026
Sherpa.ai Privacy-Preserving Multi-Party Entity Alignment without Intersection Disclosure for Noisy Identifiers
The paper introduces Sherpa.ai, a multi-party Private Set Union (PSU) protocol that enables privacy-preserving entity alignment for Vertical Federated Learning (VFL) without disclosing shared sample identities.
GuidaPA: Privacy-Preserving Chatbot for Public Administration via Federated Learning
The paper introduces GuidaPA, a privacy-preserving chatbot for public administration trained using Federated Learning, demonstrating that high-quality domain-specific AI can be achieved without centralizing sensitive organizational data.
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Papers
cs.AIcs.CLcs.DCRecentMay 31, 2026
GuidaPA: Privacy-Preserving Chatbot for Public Administration via Federated Learning
The paper introduces GuidaPA, a privacy-preserving chatbot for public administration trained using Federated Learning, demonstrating that high-quality domain-specific AI can be achieved without centra…
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cs.CRcs.AIcs.DCRecentApr 21, 2026