ZKMLOps is an MLOps framework that uses zero-knowledge proofs to generate verifiable cryptographic evidence of AI model compliance without revealing confidential information.
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Pith papers citing it
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2025 2verdicts
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PrivaDE is a privacy-preserving protocol for jointly computing data utility scores in ML using secure computation, with optimizations for efficiency and blockchain integration via smart contracts.
citing papers explorer
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"Show Me You Comply... Without Showing Me Anything": Zero-Knowledge Software Auditing for AI-Enabled Systems
ZKMLOps is an MLOps framework that uses zero-knowledge proofs to generate verifiable cryptographic evidence of AI model compliance without revealing confidential information.
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PrivaDE: Privacy-preserving Data Evaluation for Blockchain-based Data Marketplaces
PrivaDE is a privacy-preserving protocol for jointly computing data utility scores in ML using secure computation, with optimizations for efficiency and blockchain integration via smart contracts.