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This paper introduces GLoRA, a gauge-aware server representation for Federated LoRA that addresses the semantic mismatch in factor aggregation by estimating a consensus update subspace. Experiments show GLoRA outperforms baselines in performance and efficiency across heterogeneous client scenarios.
This article recommends a video that systematically explains the 10 core papers shaping today's AI industry, covering Transformer, LoRA, RAG, Agents, and the MCP protocol, aiming to help engineers clarify the technological lineage.