Subword Embeddings

Subword embeddings represent words as sequences of smaller units (subwords), improving handling of rare or unseen words in natural language processing. Current research focuses on optimizing subword segmentation algorithms, exploring the interplay between subword representations and cross-lingual transfer in multilingual models, and developing efficient methods for initializing embeddings in low-resource languages. These advancements enhance the performance of various NLP tasks, including machine translation and part-of-speech tagging, particularly for languages with complex morphology or limited training data, and contribute to more efficient and environmentally friendly model training.