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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 101–125 of 555 papers

TitleStatusHype
Rethinking Annotation: Can Language Learners Contribute?—0
CSS: Combining Self-training and Self-supervised Learning for Few-shot Dialogue State Tracking—0
U3E: Unsupervised and Erasure-based Evidence Extraction for Machine Reading Comprehension—0
Modular Approach to Machine Reading Comprehension: Mixture of Task-Aware Experts—0
To What Extent Do Natural Language Understanding Datasets Correlate to Logical Reasoning? A Method for Diagnosing Logical Reasoning.—0
Document-level Event Factuality Identification via Machine Reading Comprehension Frameworks with Transfer Learning—0
DoSEA: A Domain-specific Entity-aware Framework for Cross-Domain Named Entity RecogitionCode0
View Dialogue in 2D: A Two-stream Model in Time-speaker Perspective for Dialogue Summarization and beyond—0
Aspect-based Sentiment Analysis as Machine Reading Comprehension—0
基于相似度进行句子选择的机器阅读理解数据增强(Machine reading comprehension data Augmentation for sentence selection based on similarity)—0
基于话头话体共享结构信息的机器阅读理解研究(Rearch on Machine reading comprehension based on shared structure information between Naming and Telling)—0
DIFM:An effective deep interaction and fusion model for sentence matching—0
ET5: A Novel End-to-end Framework for Conversational Machine Reading ComprehensionCode0
Robust Domain Adaptation for Machine Reading Comprehension—0
A Multi-turn Machine Reading Comprehension Framework with Rethink Mechanism for Emotion-Cause Pair ExtractionCode1
A Survey on Measuring and Mitigating Reasoning Shortcuts in Machine Reading Comprehension—0
Unsupervised Domain Adaptation on Question-Answering System with Conversation Data—0
Large-scale Multi-granular Concept Extraction Based on Machine Reading ComprehensionCode0
Trigger-free Event Detection via Derangement Reading Comprehension—0
Exploring and Exploiting Multi-Granularity Representations for Machine Reading Comprehension—0
Continual Machine Reading Comprehension via Uncertainty-aware Fixed Memory and Adversarial Domain Adaptation—0
Act-Aware Slot-Value Predicting in Multi-Domain Dialogue State TrackingCode0
To Answer or Not to Answer? Improving Machine Reading Comprehension Model with Span-based Contrastive Learning—0
MRCLens: an MRC Dataset Bias Detection Toolkit—0
Exploiting Word Semantics to Enrich Character Representations of Chinese Pre-trained ModelsCode0
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