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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 251–300 of 555 papers

TitleStatusHype
Challenges in Procedural Multimodal Machine Comprehension:A Novel Way To Benchmark—0
A Unified Abstractive Model for Generating Question-Answer Pairs—0
Know your tools well: Better and faster QA with synthetic examples—0
Cooperative Semi-Supervised Transfer Learning of Machine Reading Comprehension—0
Multi-tasking Dialogue Comprehension with Discourse ParsingCode0
A Study on Contextualized Language Modeling for Machine Reading Comprehension—0
Interpretable Semantic Role Relation Table for Supporting Facts Recognition of Reading Comprehension—0
Analysing the Effect of Masking Length Distribution of MLM: An Evaluation Framework and Case Study on Chinese MRC Datasets—0
Logic Pre-Training of Language Models—0
More Than Reading Comprehension: A Survey on Datasets and Metrics of Textual Question Answering—0
Machine Reading Comprehension: Generative or Extractive Reader?—0
Numerical reasoning in machine reading comprehension tasks: are we there yet?—0
Abstract, Rationale, Stance: A Joint Model for Scientific Claim VerificationCode0
Relying on Discourse Analysis to Answer Complex Questions by Neural Machine Reading Comprehension—0
Decoupled Transformer for Scalable Inference in Open-domain Question Answering—0
Unsupervised Open-Domain Question Answering—0
Multilingual Multi-Aspect Explainability Analyses on Machine Reading Comprehension ModelsCode0
EviDR: Evidence-Emphasized Discrete Reasoning for Reasoning Machine Reading ComprehensionCode0
A New Entity Extraction Method Based on Machine Reading Comprehension—0
An Intelligent Recommendation-cum-Reminder System—0
Decoupled Transformer for Scalable Inference in Open-domain Question Answering—0
Ti-Reader: 基于注意力机制的藏文机器阅读理解端到端网络模型(Ti-Reader: An End-to-End Network Model Based on Attention Mechanisms for Tibetan Machine Reading Comprehension)—0
Topic Knowledge Acquisition and Utilization for Machine Reading Comprehension in Social Media Domain—0
Multi-Strategy Knowledge Distillation Based Teacher-Student Framework for Machine Reading Comprehension—0
Attention-based Aspect Reasoning for Knowledge Base Question Answering on Clinical Notes—0
基于小句复合体的中文机器阅读理解研究(Machine Reading Comprehension Based on Clause Complex)—0
DuReader\_robust: A Chinese Dataset Towards Evaluating Robustness and Generalization of Machine Reading Comprehension in Real-World ApplicationsCode0
Addressing Semantic Drift in Generative Question Answering with Auxiliary Extraction—0
Leveraging Type Descriptions for Zero-shot Named Entity Recognition and Classification—0
A Chinese Machine Reading Comprehension Dataset Automatic Generated Based on Knowledge Graph—0
面向机器阅读理解的高质量藏语数据集构建(Construction of High-quality Tibetan Dataset for Machine Reading Comprehension)—0
Sequence Model with Self-Adaptive Sliding Window for Efficient Spoken Document SegmentationCode0
Bridging the Gap between Language Model and Reading Comprehension: Unsupervised MRC via Self-Supervision—0
Automatic Task Requirements Writing Evaluation via Machine Reading ComprehensionCode0
Audio-Oriented Multimodal Machine Comprehension: Task, Dataset and Model—0
ClueReader: Heterogeneous Graph Attention Network for Multi-hop Machine Reading Comprehension—0
Ensemble Learning-Based Approach for Improving Generalization Capability of Machine Reading Comprehension Systems—0
Zero-Shot Estimation of Base Models' Weights in Ensemble of Machine Reading Comprehension Systems for Robust Generalization—0
PALRACE: Reading Comprehension Dataset with Human Data and Labeled Rationales—0
What is Missing in Existing Multi-hop Datasets? Toward Deeper Multi-hop Reasoning Task—0
Cheap and Good? Simple and Effective Data Augmentation for Low Resource Machine ReadingCode0
Adversarial Training for Machine Reading Comprehension with Virtual Embeddings—0
Bilingual Alignment Pre-Training for Zero-Shot Cross-Lingual TransferCode0
Does Structure Matter? Encoding Documents for Machine Reading Comprehension—0
RECONSIDER: Improved Re-Ranking using Span-Focused Cross-Attention for Open Domain Question Answering—0
THG: Transformer with Hyperbolic Geometry—0
NEUer at SemEval-2021 Task 4: Complete Summary Representation by Filling Answers into Question for Matching Reading Comprehension—0
Using Adversarial Attacks to Reveal the Statistical Bias in Machine Reading Comprehension Models—0
Sentence Extraction-Based Machine Reading Comprehension for Vietnamese—0
Question-Driven Span Labeling Model for Aspect–Opinion Pair Extraction—0
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