Answer Retrieval

Answer retrieval focuses on efficiently finding relevant information to answer user queries, primarily using large language models (LLMs) to improve accuracy and relevance. Current research emphasizes improving retrieval efficiency through adaptive methods that determine when retrieval is necessary, enhancing the quality of retrieved information via techniques like question rewriting and knowledge filtering, and personalizing responses based on user profiles. These advancements are significant for improving the performance of question-answering systems and conversational AI, impacting fields ranging from customer service to medical information access.