Document Question Answering

Document Question Answering (DQA) focuses on developing systems that can accurately answer questions posed about information contained within one or more documents, aiming to bridge the gap between human information needs and the vast amount of textual data available. Current research emphasizes improving the handling of long documents and multiple, potentially disparate, sources of information, often employing large language models (LLMs) augmented with retrieval mechanisms (e.g., Retrieval-Augmented Generation or RAG) and knowledge graphs to enhance reasoning and context understanding. These advancements are crucial for efficiently extracting knowledge from complex documents, impacting fields like scientific literature analysis, legal research, and general information access.