Enhancing Low-Resource Indian Language Machine Translation Using Large Language Models With Preference Optimization and Hypergeometric-Gamma Reward
TL;DR
This study introduces a preference-based learning approach using reinforcement learning to enhance machine translation for low-resource Indian languages, addressing data scarcity with large language models and hypergeometric-gamma reward optimization.
Enhancing Low-Resource Indian Language Machine Translation Using Large Language Models With Preference Optimization and Hypergeometric-Gamma Reward
Aarathi Rajagopalan Nair; Deepa Gupta; Biswajit Paul; J. Siva Bhavani
https://doi.org/10.1109/ACCESS.2025.3648480
Volume 14
Machine translation has advanced considerably in recent years yet producing accurate and natural translations remains challenging for languages with limited digital resources. The scarcity of high-quality parallel data particularly hampers the performance of models in low-resource languages. This study introduces a preference-based learning approach grounded in reinforcement learning principles to...