Multi Hop Question Answering

Multi-hop question answering (MQA) focuses on developing AI systems capable of answering complex questions requiring the integration of information from multiple sources. Current research emphasizes improving the accuracy and efficiency of MQA systems, particularly through advancements in retrieval-augmented generation models, hierarchical reasoning frameworks, and the incorporation of structured knowledge graphs. These efforts are driven by the need for more robust and explainable AI systems, with significant implications for applications ranging from open-domain question answering to knowledge base querying and scientific literature analysis.