Machine Reading Comprehension

QASC: A Dataset for Question Answering via Sentence Composition AAAI 2020 Q. Can Knowledge Graphs be used to Answer Boolean Questions? A. It’s complicated! EMNLP 2020 Question Answering with Long Multiple-Span Answers EMNLP 2020 Question Directed Graph Attention Network for Numerical Reasoning over Text EMNLP 2020 R4C: A Benchmark for Evaluating RC Systems to Get the Right Answer for the Right Reason ACL 2020 Rception: Wide and Deep Interaction Networks for Machine Reading Comprehension (Student Abstract) AAAI 2020 Read and Reason with MuSeRC and RuCoS: Datasets for Machine Reading Comprehension for Russian COLING 2020 Reading Comprehension as Natural Language Inference:A Semantic Analysis COLING 2020 ReCO: A Large Scale Chinese Reading Comprehension Dataset on Opinion AAAI 2020 Recurrent Chunking Mechanisms for Long-Text Machine Reading Comprehension ACL 2020 RikiNet: Reading Wikipedia Pages for Natural Question Answering ACL 2020 Robust Machine Reading Comprehension by Learning Soft labels COLING 2020 SCDE: Sentence Cloze Dataset with High Quality Distractors From Examinations ACL 2020 Scene Restoring for Narrative Machine Reading Comprehension EMNLP 2020 Seeing the World through Text: Evaluating Image Descriptions for Commonsense Reasoning in Machine Reading Comprehension COLING 2020 Segment-Then-Rank: Non-Factoid Question Answering on Instructional Videos AAAI 2020 Semantics-Aware BERT for Language Understanding AAAI 2020 SG-Net: Syntax-Guided Machine Reading Comprehension AAAI 2020 Span Selection Pre-training for Question Answering ACL 2020 SQL Generation via Machine Reading Comprehension COLING 2020 SRLGRN: Semantic Role Labeling Graph Reasoning Network EMNLP 2020 STARC: Structured Annotations for Reading Comprehension ACL 2020 Teaching Machine Comprehension with Compositional Explanations EMNLP 2020 Tell Me How to Ask Again: Question Data Augmentation with Controllable Rewriting in Continuous Space EMNLP 2020 The Language Interpretability Tool: Extensible, Interactive Visualizations and Analysis for NLP Models EMNLP 2020