The paper delivers a systematization of knowledge on AI agent-blockchain interactions via a bidirectional trust framework, an Agent-Blockchain Interaction Model, a five-dimensional evaluation lens, and nine identified open problems.
Zero-Knowledge Proofs of Training for Deep Neural Networks
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ZKMLOps is an MLOps framework that uses zero-knowledge proofs to generate verifiable cryptographic evidence of AI model compliance without revealing confidential information.
LAMa reconstructs plaintext coordinates in multi-dimensional encrypted range queries from access-pattern leakage and known query distribution, with the first rigorous guarantees on query complexity and reconstruction quality.
citing papers explorer
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Toward Web 4.0: Bidirectional Trust between AI Agents and Blockchain
The paper delivers a systematization of knowledge on AI agent-blockchain interactions via a bidirectional trust framework, an Agent-Blockchain Interaction Model, a five-dimensional evaluation lens, and nine identified open problems.
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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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How Query Distribution Knowledge Breaks Multidimensional Encrypted Range Queries, With Guarantees
LAMa reconstructs plaintext coordinates in multi-dimensional encrypted range queries from access-pattern leakage and known query distribution, with the first rigorous guarantees on query complexity and reconstruction quality.