NLP Problem

Natural Language Processing (NLP) research aims to enable computers to understand, interpret, and generate human language. Current efforts focus on improving the efficiency and effectiveness of large language models (LLMs) for various tasks, including named entity recognition and text classification, often incorporating techniques like neural-symbolic approaches and data augmentation to enhance performance and address resource limitations. This research is significant because it drives advancements in applications ranging from legal tech and healthcare to improved accessibility for under-resourced languages, while also prompting critical evaluation of model performance beyond simple accuracy metrics, considering factors like energy consumption and ethical implications.

Papers