Ad Hoc Retrieval

Ad hoc retrieval focuses on efficiently finding relevant documents from a large collection in response to a user's information need, a crucial task in various applications. Current research emphasizes improving the accuracy and efficiency of retrieval by integrating large language models (LLMs) with traditional information retrieval techniques, often employing retrieval-augmented generation (RAG) frameworks or pre-training LLMs on structured data like Wikipedia. This involves exploring strategies for optimally combining LLMs' inherent knowledge with external information sources and developing effective methods for learning query and document representations. These advancements promise significant improvements in the performance of search engines and question-answering systems across diverse domains.