Intent Label

Intent label research focuses on accurately identifying the user's goal or purpose within text or speech, crucial for applications like chatbots and recommender systems. Current research emphasizes leveraging large language models (LLMs) for improved accuracy and zero-shot capabilities, often combined with techniques like contrastive learning and data augmentation to address data scarcity and out-of-domain detection challenges. These advancements improve the performance of natural language understanding systems, leading to more effective and user-friendly applications across various domains, including customer service and personalized recommendations.