Multi Hop Machine Reading Comprehension

Multi-hop machine reading comprehension (MHRC) focuses on developing systems that can answer complex questions requiring information synthesis from multiple, disparate sources within a text. Current research emphasizes improving model architectures to effectively integrate information across these sources, often leveraging techniques like graph neural networks and incorporating external knowledge bases to enhance accuracy. This field is significant because it advances natural language processing capabilities, with applications ranging from improved medical diagnosis support (e.g., predicting drug interactions) to enabling more sophisticated human-robot collaboration.