Query Set

Query sets are crucial for various machine learning tasks, particularly in expanding taxonomies and improving retrieval-augmented generation. Current research focuses on efficiently handling large and potentially imbalanced query sets, employing techniques like large language models (LLMs) to generate and analyze queries, and leveraging graph neural networks and contrastive learning to improve the accuracy of classification and relation extraction within these sets. These advancements are improving the performance of applications ranging from digital health chatbots to e-commerce product categorization, leading to more accurate and robust systems.