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Adversarial Robustness in Machine Learning

Работ: 56

  1. Decoupling Evidence from Execution: A Zero-Knowledge Runtime Authority and Dynamic Refusal Protocol for Agentic AI

    Siddiqui Jameel Ahmed

    ПрепринтScientific Computing and Data ManagementZenodo (CERN European Organization for Nuclear Research)2026Цитирований: 0
    ABI

  2. Authorization Architectures for AI-Driven Critical Infrastructure: Runtime Authorization for AI-Assisted Decision Systems in Nuclear and Renewable Energy Environments

    Edward Meyman

    ПрепринтAdversarial Robustness in Machine LearningZenodo (CERN European Organization for Nuclear Research)2026Цитирований: 0
    ABI

  3. Authorization Architectures for AI-Driven Critical Infrastructure: Runtime Authorization for AI-Assisted Decision Systems in Nuclear and Renewable Energy Environments

    Edward Meyman

    ПрепринтAdversarial Robustness in Machine LearningZenodo (CERN European Organization for Nuclear Research)2026Цитирований: 0
    ABI

  4. Model-to-Model Collision (M2MC): A Conceptual Framework for Quantifying Cross-Model Semantic Invalidation in Autonomous Multi-Vendor AI Ecosystems

    Siddiqui Jameel Ahmed

    ПрепринтSoftware System Performance and ReliabilityZenodo (CERN European Organization for Nuclear Research)2026Цитирований: 0
    ABI

  5. Model-to-Model Collision (M2MC): A Conceptual Framework for Quantifying Cross-Model Semantic Invalidation in Autonomous Multi-Vendor AI Ecosystems

    Siddiqui Jameel Ahmed

    ПрепринтSoftware System Performance and ReliabilityZenodo (CERN European Organization for Nuclear Research)2026Цитирований: 0
    ABI

  6. Authorization Architectures for AI-Driven Critical Infrastructure: Runtime Authorization for AI-Assisted Decision Systems in Nuclear and Renewable Energy Environments

    Edward Meyman

    ПрепринтAccess Control and TrustSSRN Electronic Journal2026Цитирований: 0
    ABI