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We classify contributions along two directions: AI-enhanced DLT, and DLT-enhanced AI. In the first case, we examine how AI techniques improve DLT systems across five layers: data, network, consensus, execution, and application layers.\n  In the second case, we analyse how DLT supports AI systems across five layers: infrastructure, data, model, inference, and application layers, with particular attention to federated learning, model evaluation, and multi-agent coordination.\n  T","title":"SoK: A Systematic Bidirectional Literature Review of AI & DLT Convergence","url":"https://arxiv.org/abs/2605.10515","vendor":"arxiv_cs_ai"},"summary":"arXiv:2605.10515v1 Announce Type: cross \nAbstract: The integration of Artificial Intelligence (AI) with Distributed Ledger Technology (DLT) has become a growing research area, yet contributions tend to cluster around specific application domains or examine only one direction of the integration, leaving the broader architectural interplay between the two technologies poorly understood.\n  This work addresses that gap through a structured, bidirectional review of peer-reviewed studies published between 2020 and 2025. 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