Book Question Answering

Book question answering (QA) focuses on enabling computer systems to answer questions using only their pre-existing knowledge, without access to external resources like the internet. Current research emphasizes improving the accuracy and trustworthiness of these systems, particularly by addressing issues like hallucinations (generating incorrect information) and efficiently leveraging internal knowledge representations. This involves exploring various model architectures, including those incorporating contrastive learning, parameter-efficient fine-tuning, and methods for dynamically selecting and utilizing internal knowledge based on confidence levels. Advances in this area are crucial for developing more reliable and robust AI systems across diverse applications.