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Machine Reading Comprehension

966 directly classified papers

Papers per year

Papers

COVID-QA: A Question Answering Dataset for COVID-19 ACL 2020
INFOTABS: Inference on Tables as Semi-structured Data ACL 2020
R4C: A Benchmark for Evaluating RC Systems to Get the Right Answer for the Right Reason ACL 2020
Benefits of Intermediate Annotations in Reading Comprehension ACL 2020
Segment-Then-Rank: Non-Factoid Question Answering on Instructional Videos AAAI 2020
An Empirical Study of Content Understanding in Conversational Question Answering AAAI 2020
DCMN+: Dual Co-Matching Network for Multi-Choice Reading Comprehension AAAI 2020
JEC-QA: A Legal-Domain Question Answering Dataset AAAI 2020
Rception: Wide and Deep Interaction Networks for Machine Reading Comprehension (Student Abstract) AAAI 2020
Interactive Machine Comprehension with Information Seeking Agents ACL 2020
STARC: Structured Annotations for Reading Comprehension ACL 2020
A Self-Training Method for Machine Reading Comprehension with Soft Evidence Extraction ACL 2020
Machine Reading of Historical Events ACL 2020
Dynamic Sampling Strategies for Multi-Task Reading Comprehension ACL 2020
Enhancing Answer Boundary Detection for Multilingual Machine Reading Comprehension ACL 2020
The TechQA Dataset ACL 2020
Recurrent Chunking Mechanisms for Long-Text Machine Reading Comprehension ACL 2020
Context-based Automated Scoring of Complex Mathematical Responses ACL 2020
A Unified MRC Framework for Named Entity Recognition ACL 2020
Learning to Explain: Datasets and Models for Identifying Valid Reasoning Chains in Multihop Question-Answering EMNLP 2020
Grounded Adaptation for Zero-shot Executable Semantic Parsing EMNLP 2020
SRLGRN: Semantic Role Labeling Graph Reasoning Network EMNLP 2020
The Language Interpretability Tool: Extensible, Interactive Visualizations and Analysis for NLP Models EMNLP 2020
Learning to Classify the Wrong Answers for Multiple Choice Question Answering (Student Abstract) AAAI 2020
Assessing the Benchmarking Capacity of Machine Reading Comprehension Datasets AAAI 2020