DeFiRank: Federated Pairwise Ranking for Governance in Decentralized Financial Networks

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Researchers have proposed DeFiRank, a system that uses federated learning to rank the importance of participants in decentralized finance networks. Instead of relying on manual committees or simple token counts, it lets institutions train models on private data to identify high-value network behavior. This attempts to solve the bottleneck of human-led governance while maintaining data privacy.