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Found 2 papers, 1 papers with code
FedCAda: Adaptive Client-Side Optimization for Accelerated and Stable Federated Learning
This comparative analysis revealed that due to the limited information contained within client models from other clients during the initial stages of federated learning, more substantial constraints need to be imposed on the parameters of the adaptive algorithm.
$R^3$-NL2GQL: A Hybrid Models Approach for for Accuracy Enhancing and Hallucinations Mitigation
While current NL2SQL tasks constructed using Foundation Models have achieved commendable results, their direct application to Natural Language to Graph Query Language (NL2GQL) tasks poses challenges due to the significant differences between GQL and SQL expressions, as well as the numerous types of GQL.
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