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
What company do words keep? Revisiting the distributional semantics of J.R. Firth & Zellig Harris
Mikael Brunila, Jack LaViolette
Assessing the Limits of the Distributional Hypothesis in Semantic Spaces: Trait-based Relational Knowledge and the Impact of Co-occurrences
Mark Anderson, Jose Camacho-Collados