2 papers
cs.DB2026
DexterSQL: Deep Schema Exploration and Rule-based Correction for Text-to-SQL Generation
Anik Pramanik, Murat Kantarcioglu, Vincent Oria +1
Prompting-based (i.e., non-fine-tuning) Text-to-SQL methods, where underlying large language model parameters are not changed for the task, face three problems: (i) relying on coar…
cs.LG2026
FedDAG: Clustered Federated Learning via Global Data and Gradient Integration for Heterogeneous Environments
Anik Pramanik, Murat Kantarcioglu, Vincent Oria +1
Federated Learning (FL) enables a group of clients to collaboratively train a model without sharing individual data, but its performance drops when client data are heterogeneous. C…