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Southeast University, Southeast University)
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Federated learning can overcome data silos, but struggles when clients have different label relationships; FedHarmony shows how to harmonize these differences, leading to better performance.
MLLMs can slash image annotation costs by 1000x while TagLLM closes the performance gap with human annotations by 60-80%.
