4 papers
Inducing Robustness in a 2 Dimensional Direct Preference Optimization Paradigm
Sarvesh Shashidhar, Ritik, Nachiketa Patil +2
Direct Preference Optimisation (DPO) has emerged as a powerful method for aligning Large Language Models (LLMs) with human preferences, offering a stable and efficient alternative…
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…
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…
GUIDEQ: Framework for Guided Questioning for progressive informational collection and classification
Priya Mishra, Suraj Racha, Kaustubh Ponkshe +2
Question Answering (QA) is an important part of tasks like text classification through information gathering. These are finding increasing use in sectors like healthcare, customer…