Multi Choice Machine Reading Comprehension

Multi-choice machine reading comprehension (MRC) focuses on enabling computers to answer questions by selecting the correct answer from a set of options, given a relevant passage of text. Current research emphasizes improving model performance through techniques like fine-tuning and prompt-tuning pre-trained language models (PLMs), as well as developing methods to better leverage knowledge transfer across different MRC tasks and improve the quality of distractor options in multiple-choice questions. This area is significant because it advances natural language understanding capabilities and has practical applications in automated assessment, question answering systems, and information retrieval.