Query Document Pair

Query-document pairs are fundamental units in information retrieval, representing the core relationship between a user's search query and a relevant document. Current research focuses on improving the efficiency and accuracy of retrieving these pairs, employing techniques like large language models (LLMs) to generate synthetic pairs for training, and developing novel architectures such as decentralized differentiable search indices and encoder-decoder models for faster inference. These advancements aim to enhance the performance of search engines and related applications by addressing challenges like noisy data and the need for scalable, efficient retrieval systems.