Open Domain QA

Open-domain question answering (QA) aims to build systems capable of answering questions on any topic, leveraging vast amounts of external knowledge. Current research heavily focuses on improving retrieval-augmented generation (RAG) models, which combine large language models with external knowledge retrieval, addressing challenges like irrelevant context retrieval and efficient knowledge utilization. Significant effort is also dedicated to enhancing the reasoning capabilities of these models and developing methods for verifying answer accuracy, including analyzing the reasoning steps generated by the models. These advancements hold considerable promise for improving access to information and facilitating knowledge-intensive tasks across various domains, from scientific research to e-governance.