Machine Reading Comprehension: a Literature Review
Xin Zhang, An Yang, Sujian Li, Yizhong Wang
TL;DR
This literature review summarizes recent advances in machine reading comprehension, focusing on datasets and techniques, highlighting key characteristics and approaches in the field.
Contribution
It provides a comprehensive overview of recent MRC corpora and techniques, offering insights into their characteristics and development.
Findings
Comparison of various MRC datasets
Description of key MRC techniques
Identification of challenges and future directions
Abstract
Machine reading comprehension aims to teach machines to understand a text like a human and is a new challenging direction in Artificial Intelligence. This article summarizes recent advances in MRC, mainly focusing on two aspects (i.e., corpus and techniques). The specific characteristics of various MRC corpus are listed and compared. The main ideas of some typical MRC techniques are also described.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsTopic Modeling · Natural Language Processing Techniques · Multimodal Machine Learning Applications