<ul><li>Federated Learning (FL) is gaining popularity for collaborative model training while maintaining data privacy among decentralized participants.</li><li>A new benchmark called ATR-Bench is introduced to analyze federated learning based on three core dimensions: Adaptation, Trust, and Reasoning.</li><li>ATR-Bench aims to standardize evaluation criteria for FL methods, addressing practical challenges and enabling fair comparisons.</li><li>The framework includes benchmarking methods and datasets for adaptation to diverse clients, assessing trustworthiness in challenging environments, and offering insights on reasoning in FL.</li></ul>

ATR-Bench: A Federated Learning Benchmark for Adaptation, Trust, and Reasoning

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