This repository serves as a curated collection of seminal papers in Machine Reading Comprehension (MRC), aimed at researchers and practitioners in Natural Language Processing (NLP). It provides a structured overview of key advancements, models, and datasets that have shaped the field.

How It Works

The project compiles a comprehensive list of influential research papers, categorizing them by their contributions to MRC. It highlights various model architectures, including Memory Networks, Attention-based models, and Transformer variants, alongside significant datasets like SQuAD, MS MARCO, and TriviaQA. This curated list facilitates a historical and technical understanding of MRC evolution.

Highlighted Details

• Extensive coverage of foundational and recent MRC papers.
• Includes key model architectures and their associated publications.
• Lists major datasets used for evaluating MRC systems.
• Provides links to papers for direct access to research.

Maintenance & Community

This project is contributed by Yankai Lin, Deming Ye, and Haozhe Ji. Further community contributions are welcome.

Licensing & Compatibility

The repository itself does not appear to have a specific license mentioned in the README. It is a collection of links to research papers, which are governed by their respective publication licenses.

Limitations & Caveats

This is a curated list of papers and does not include code implementations or direct access to the papers themselves, only references. The content is focused solely on MRC and does not cover broader question-answering or NLP tasks.