Vocabulary Transfer

Vocabulary transfer in natural language processing involves adapting a pre-trained language model's vocabulary to a specific domain or task by incorporating corpus-specific tokens during fine-tuning. Current research focuses on leveraging this technique to improve model performance on downstream tasks, particularly in specialized domains like medicine and languages with significant loanwords, often using transformer-based architectures. This approach offers significant benefits, including enhanced accuracy and reduced model size and inference time, impacting both the efficiency and effectiveness of various natural language processing applications.