NLP Field
Natural Language Processing (NLP) focuses on enabling computers to understand, interpret, and generate human language. Current research emphasizes improving model performance across diverse tasks, including question answering, text classification, and information extraction, often leveraging large language models (LLMs) and transformer architectures. These advancements are significantly impacting various fields, from healthcare (e.g., dementia detection, clinical data analysis) and legal (e.g., document processing, legal reasoning) to education and cybersecurity, by automating tasks and providing new analytical capabilities. A key challenge remains ensuring fairness, mitigating biases, and addressing privacy concerns within these powerful models.
Papers
Dim Wihl Gat Tun: The Case for Linguistic Expertise in NLP for Underdocumented Languages
Clarissa Forbes, Farhan Samir, Bruce Harold Oliver, Changbing Yang, Edith Coates, Garrett Nicolai, Miikka Silfverberg
Expanding Pretrained Models to Thousands More Languages via Lexicon-based Adaptation
Xinyi Wang, Sebastian Ruder, Graham Neubig