ViConBERT: Context-Gloss Aligned Vietnamese Word Embedding for Polysemous and Sense-Aware Representations

The article introduces ViConBERT, a model designed for Vietnamese language processing. It focuses on addressing the challenges of polysemy (words with multiple meanings) and aims to create word embeddings that are sensitive to different word senses. The use of context and gloss alignment suggests an approach that leverages both the surrounding words and dictionary definitions to improve the model's understanding of word meanings. The source being ArXiv indicates this is a research paper, likely detailing the model's architecture, training process, and evaluation results.