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cs.LG2025
Subset Selection for Fine-Tuning: A Utility-Diversity Balanced Approach for Mathematical Domain Adaptation
Madhav Kotecha, Vijendra Kumar Vaishya, Smita Gautam +1
We propose a refined approach to efficiently fine-tune large language models (LLMs) on specific domains like the mathematical domain by employing a budgeted subset selection method…
cs.LG2024
Framework for Co-distillation Driven Federated Learning to Address Class Imbalance in Healthcare
Suraj Racha, Shubh Gupta, Humaira Firdowse +3
Federated Learning (FL) is a pioneering approach in distributed machine learning, enabling collaborative model training across multiple clients while retaining data privacy. Howeve…