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
Privacy- and Utility-Preserving NLP with Anonymized Data: A case study of Pseudonymization
Oleksandr Yermilov, Vipul Raheja, Artem Chernodub
The economic trade-offs of large language models: A case study
Kristen Howell, Gwen Christian, Pavel Fomitchov, Gitit Kehat, Julianne Marzulla, Leanne Rolston, Jadin Tredup, Ilana Zimmerman, Ethan Selfridge, Joseph Bradley