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Machine Reading Comprehension

Machine Reading Comprehension is one of the key problems in Natural Language Understanding, where the task is to read and comprehend a given text passage, and then answer questions based on it.

Source: Making Neural Machine Reading Comprehension Faster

Papers

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Showing 351–400 of 555 papers

TitleStatusHype
Seeing the World through Text: Evaluating Image Descriptions for Commonsense Reasoning in Machine Reading Comprehension—0
SQL Generation via Machine Reading ComprehensionCode0
Unsupervised Explanation Generation for Machine Reading Comprehension—0
CalibreNet: Calibration Networks for Multilingual Sequence Labeling—0
Synonym Knowledge Enhanced Reader for Chinese Idiom Reading ComprehensionCode0
Answer Span Correction in Machine Reading Comprehension—0
From Dataset Recycling to Multi-Property Extraction and BeyondCode0
Improving Machine Reading Comprehension with Single-choice Decision and Transfer Learning—0
Correcting the Misuse: A Method for the Chinese Idiom Cloze Test—0
Towards Medical Machine Reading Comprehension with Structural Knowledge and Plain Text—0
Q. Can Knowledge Graphs be used to Answer Boolean Questions? A. It’s complicated!—0
Event Extraction as Machine Reading Comprehension—0
Scene Restoring for Narrative Machine Reading Comprehension—0
Cross-lingual Machine Reading Comprehension with Language Branch Knowledge Distillation—0
QBSUM: a Large-Scale Query-Based Document Summarization Dataset from Real-world Applications—0
Improved Synthetic Training for Reading Comprehension—0
Bi-directional Cognitive Thinking Network for Machine Reading Comprehension—0
Interpreting Attention Models with Human Visual Attention in Machine Reading Comprehension—0
Context Modeling with Evidence Filter for Multiple Choice Question Answering—0
Tell Me How to Ask Again: Question Data Augmentation with Controllable Rewriting in Continuous SpaceCode0
ARES: A Reading Comprehension Ensembling Service—0
A Survey on Explainability in Machine Reading Comprehension—0
A Vietnamese Dataset for Evaluating Machine Reading Comprehension—0
Bridging Information-Seeking Human Gaze and Machine Reading Comprehension—0
MaP: A Matrix-based Prediction Approach to Improve Span Extraction in Machine Reading Comprehension—0
No Answer is Better Than Wrong Answer: A Reflection Model for Document Level Machine Reading Comprehension—0
Question Directed Graph Attention Network for Numerical Reasoning over TextCode0
Multi-span Style Extraction for Generative Reading Comprehension—0
Composing Answer from Multi-spans for Reading Comprehension—0
Improving Machine Reading Comprehension with Contextualized Commonsense Knowledge—0
Revisiting the Open-Domain Question Answering Pipeline—0
Continual Domain Adaptation for Machine Reading Comprehension—0
Knowledge-Empowered Representation Learning for Chinese Medical Reading Comprehension: Task, Model and ResourcesCode0
Applications of BERT Based Sequence Tagging Models on Chinese Medical Text Attributes Extraction—0
An Experimental Study of Deep Neural Network Models for Vietnamese Multiple-Choice Reading Comprehension—0
App-Aware Response Synthesis for User Reviews—0
Multi-source Meta Transfer for Low Resource Multiple-Choice Question Answering—0
A Frame-based Sentence Representation for Machine Reading Comprehension—0
Low-Resource Generation of Multi-hop Reasoning Questions—0
A Survey on Machine Reading Comprehension: Tasks, Evaluation Metrics and Benchmark Datasets—0
New Vietnamese Corpus for Machine Reading Comprehension of Health News Articles—0
On the Multi-Property Extraction and Beyond—0
Interpreting Attention Models with Human Visual Attention in Machine Reading Comprehension—0
A Pairwise Probe for Understanding BERT Fine-Tuning on Machine Reading Comprehension—0
Conversational Machine Comprehension: a Literature Review—0
Analyse automatique en cadres s\'emantiques pour l'apprentissage de mod\`eles de compr\'ehension de texte (Semantic Frame Parsing for training Machine Reading Comprehension models)—0
BIOMRC: A Dataset for Biomedical Machine Reading ComprehensionCode0
To Test Machine Comprehension, Start by Defining Comprehension—0
TORQUE: A Reading Comprehension Dataset of Temporal Ordering Questions—0
SQuAD2-CR: Semi-supervised Annotation for Cause and Rationales for Unanswerability in SQuAD 2.0—0
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