Less is More: Adapting Text Embeddings for Low-Resource Languages with Small Scale Noisy Synthetic Data

Zaruhi Navasardyan, Spartak Bughdaryan, Bagrat Minasyan +1

Low-resource languages (LRLs) often lack high-quality, large-scale datasets for training effective text embedding models, hindering their application in tasks like retrieval-augmen…