Text Classifier

Text classification, the task of automatically assigning categories to text data, is a core area of natural language processing (NLP) with broad applications. Current research focuses on improving classifier robustness against adversarial attacks (e.g., subtly altered text designed to mislead), enhancing explainability through methods that align with human intuition, and leveraging large language models (LLMs) for efficient and effective classification, often with minimal training data. These advancements are crucial for building reliable and trustworthy text classifiers, impacting fields ranging from content moderation and sentiment analysis to medical diagnosis and legal document processing.