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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 126–150 of 555 papers

TitleStatusHype
Single-Sentence Reader: A Novel Approach for Addressing Answer Position BiasCode0
Integrating a Heterogeneous Graph with Entity-aware Self-attention using Relative Position Labels for Reading Comprehension Model—0
ZeQR: Zero-shot Query Reformulation for Conversational SearchCode0
Teach model to answer questions after comprehending the document—0
SciMRC: Multi-perspective Scientific Machine Reading Comprehension—0
Bidirectional End-to-End Learning of Retriever-Reader Paradigm for Entity LinkingCode0
Bridging the Gap between Decision and Logits in Decision-based Knowledge Distillation for Pre-trained Language ModelsCode0
Improving Opinion-based Question Answering Systems Through Label Error Detection and Overwrite—0
Knowing-how & Knowing-that: A New Task for Machine Comprehension of User ManualsCode0
How Many Answers Should I Give? An Empirical Study of Multi-Answer Reading ComprehensionCode0
A Causal View of Entity Bias in (Large) Language ModelsCode0
Machine Reading Comprehension using Case-based Reasoning—0
mPMR: A Multilingual Pre-trained Machine Reader at ScaleCode0
EMBRACE: Evaluation and Modifications for Boosting RACECode0
SkillQG: Learning to Generate Question for Reading Comprehension Assessment—0
NER-to-MRC: Named-Entity Recognition Completely Solving as Machine Reading Comprehension—0
Adaptive loose optimization for robust question answeringCode0
Multi-View Graph Representation Learning for Answering Hybrid Numerical Reasoning QuestionCode0
Information Extraction from Documents: Question Answering vs Token Classification in real-world setups—0
Evaluating the Robustness of Machine Reading Comprehension Models to Low Resource Entity Renaming—0
A Data-centric Framework for Improving Domain-specific Machine Reading Comprehension Datasets—0
A Multiple Choices Reading Comprehension Corpus for Vietnamese Language EducationCode0
Revealing Weaknesses of Vietnamese Language Models Through Unanswerable Questions in Machine Reading Comprehension—0
Clinical Concept and Relation Extraction Using Prompt-based Machine Reading Comprehension—0
LUKE-Graph: A Transformer-based Approach with Gated Relational Graph Attention for Cloze-style Reading Comprehension—0
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