Document Grounded Dialog

Document-grounded dialog focuses on building conversational agents that generate responses grounded in provided documents, aiming for factual and relevant interactions. Current research emphasizes improving response faithfulness to the source document, often employing neural generative models enhanced by techniques like incorporating pointwise mutual information or noisy channel models to control factuality and fluency. This area is significant due to its potential for applications in information retrieval, customer service, and education, driving the development of larger, more diverse datasets and more robust model architectures to address challenges like limited training data and diverse document structures.