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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 51–100 of 555 papers

TitleStatusHype
A Robustly Optimized BMRC for Aspect Sentiment Triplet ExtractionCode1
End-to-End Chinese Speaker IdentificationCode1
Sentence-level Event Detection without Triggers via Prompt Learning and Machine Reading ComprehensionCode1
SemEval-2021 Task 4: Reading Comprehension of Abstract MeaningCode1
Fact-driven Logical Reasoning for Machine Reading ComprehensionCode1
FewCLUE: A Chinese Few-shot Learning Evaluation BenchmarkCode1
FinBERT-MRC: financial named entity recognition using BERT under the machine reading comprehension paradigmCode1
ReCO: A Large Scale Chinese Reading Comprehension Dataset on OpinionCode1
From Machine Reading Comprehension to Dialogue State Tracking: Bridging the GapCode1
Dependency Parsing as MRC-based Span-Span PredictionCode1
Multi-Grained Query-Guided Set Prediction Network for Grounded Multimodal Named Entity RecognitionCode1
GENIUS: Sketch-based Language Model Pre-training via Extreme and Selective Masking for Text Generation and AugmentationCode1
Interactive Language Learning by Question AnsweringCode1
Learning Disentangled Semantic Representations for Zero-Shot Cross-Lingual Transfer in Multilingual Machine Reading ComprehensionCode1
A Sentence Cloze Dataset for Chinese Machine Reading ComprehensionCode1
Cooperative Self-training of Machine Reading ComprehensionCode1
Asking Effective and Diverse Questions: A Machine Reading Comprehension based Framework for Joint Entity-Relation ExtractionCode1
Asking Questions the Human Way: Scalable Question-Answer Generation from Text CorpusCode1
Interactive Machine Comprehension with Dynamic Knowledge GraphsCode1
JaQuAD: Japanese Question Answering Dataset for Machine Reading ComprehensionCode1
Logic-Guided Data Augmentation and Regularization for Consistent Question AnsweringCode1
Logiformer: A Two-Branch Graph Transformer Network for Interpretable Logical ReasoningCode1
A Multi-turn Machine Reading Comprehension Framework with Rethink Mechanism for Emotion-Cause Pair ExtractionCode1
ChineseBERT: Chinese Pretraining Enhanced by Glyph and Pinyin InformationCode1
Clinical Reading Comprehension: A Thorough Analysis of the emrQA DatasetCode1
MoEfication: Transformer Feed-forward Layers are Mixtures of ExpertsCode1
TSQA: Tabular Scenario Based Question AnsweringCode1
ComQA:Compositional Question Answering via Hierarchical Graph Neural NetworksCode1
Coreference Resolution as Query-based Span PredictionCode1
Gated Convolutional Bidirectional Attention-based Model for Off-topic Spoken Response DetectionCode0
From Dataset Recycling to Multi-Property Extraction and BeyondCode0
From Cloze to Comprehension: Retrofitting Pre-trained Masked Language Model to Pre-trained Machine ReaderCode0
GraphFlow: Exploiting Conversation Flow with Graph Neural Networks for Conversational Machine ComprehensionCode0
A Framework for Evaluation of Machine Reading Comprehension Gold StandardsCode0
An Understanding-Oriented Robust Machine Reading Comprehension ModelCode0
FedQAS: Privacy-aware machine reading comprehension with federated learningCode0
From Bag of Sentences to Document: Distantly Supervised Relation Extraction via Machine Reading ComprehensionCode0
Guiding LLM to Fool Itself: Automatically Manipulating Machine Reading Comprehension Shortcut TriggersCode0
EviDR: Evidence-Emphasized Discrete Reasoning for Reasoning Machine Reading ComprehensionCode0
Evidence Sentence Extraction for Machine Reading ComprehensionCode0
Explaining Interactions Between Text SpansCode0
ET5: A Novel End-to-end Framework for Conversational Machine Reading ComprehensionCode0
Adversarial Self-Attention for Language UnderstandingCode0
Exploiting Word Semantics to Enrich Character Representations of Chinese Pre-trained ModelsCode0
Entity-Relation Extraction as Multi-Turn Question AnsweringCode0
English Machine Reading Comprehension Datasets: A SurveyCode0
Enhancing Pre-Trained Language Representations with Rich Knowledge for Machine Reading ComprehensionCode0
EQuANt (Enhanced Question Answer Network)Code0
BioADAPT-MRC: Adversarial Learning-based Domain Adaptation Improves Biomedical Machine Reading Comprehension TaskCode0
Bilingual Alignment Pre-Training for Zero-Shot Cross-Lingual TransferCode0
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