Augmented Query

Augmented query techniques enhance information retrieval and language generation by enriching user queries with supplementary data or context. Current research focuses on leveraging relational databases, hierarchical clustering, and large language models to generate more comprehensive and effective queries, improving the accuracy and efficiency of tasks like document retrieval and summarization. These advancements are significant for improving the performance of various applications, including search engines, vulnerability reporting systems, and large language model-based systems prone to inaccuracies. The resulting improvements in information access and processing have broad implications across numerous fields.