Pre Trained Multilingual

Pre-trained multilingual models aim to leverage the shared information across multiple languages to improve natural language processing tasks, particularly in low-resource settings. Current research focuses on refining these models, investigating techniques like fine-tuning with specialized datasets (including those for under-represented languages), and mitigating biases inherent in existing architectures. This work is significant because it enables cross-lingual transfer learning, improving machine translation and other NLP applications, especially for languages with limited training data, and addressing ethical concerns around fairness and inclusivity.