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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 101–150 of 555 papers

TitleStatusHype
A3Net: Adversarial-and-Attention Network for Machine Reading Comprehension—0
Developing Dataset of Japanese Slot Filling Quizzes Designed for Evaluation of Machine Reading Comprehension—0
Deep Understanding based Multi-Document Machine Reading Comprehension—0
Bridging Information-Seeking Human Gaze and Machine Reading Comprehension—0
Answer Generation through Unified Memories over Multiple Passages—0
Bridging the Gap between Language Model and Reading Comprehension: Unsupervised MRC via Self-Supervision—0
Bridging the Gap between Language Models and Cross-Lingual Sequence Labeling—0
Bridging The Gap: Entailment Fused-T5 for Open-retrieval Conversational Machine Reading Comprehension—0
BUAP: Evaluating Features for Multilingual and Cross-Level Semantic Textual Similarity—0
Building Dynamic Knowledge Graphs from Text using Machine Reading Comprehension—0
Answerable or Not: Devising a Dataset for Extending Machine Reading Comprehension—0
An MRC Framework for Semantic Role Labeling—0
CALOR-QUEST : generating a training corpus for Machine Reading Comprehension models from shallow semantic annotations—0
CALOR-QUEST : un corpus d'entra\^ et d'\'evaluation pour la compr\'ehension automatique de textes (Machine reading comprehension is a task related to Question-Answering where questions are not generic in scope but are related to a particular document)—0
A Comprehensive Survey on Multi-hop Machine Reading Comprehension Approaches—0
Can GPT Redefine Medical Understanding? Evaluating GPT on Biomedical Machine Reading Comprehension—0
CFO: A Framework for Building Production NLP Systems—0
Challenges in Procedural Multimodal Machine Comprehension:A Novel Way To Benchmark—0
Enhancing lexical-based approach with external knowledge for Vietnamese multiple-choice machine reading comprehension—0
ChemistryQA: A Complex Question Answering Dataset from Chemistry—0
Biomedical Question Answering: A Survey of Approaches and Challenges—0
Adversarial reading networks for machine comprehension—0
A Chinese Machine Reading Comprehension Dataset Automatic Generated Based on Knowledge Graph—0
CJRC: A Reliable Human-Annotated Benchmark DataSet for Chinese Judicial Reading Comprehension—0
Clinical Concept and Relation Extraction Using Prompt-based Machine Reading Comprehension—0
An Intelligent Recommendation-cum-Reminder System—0
Adversarial Domain Adaptation for Machine Reading Comprehension—0
SNFinLLM: Systematic and Nuanced Financial Domain Adaptation of Chinese Large Language Models—0
Detecting Causes of Stock Price Rise and Decline by Machine Reading Comprehension with BERT—0
Dialog State Tracking: A Neural Reading Comprehension Approach—0
Dual Multi-head Co-attention for Multi-choice Reading Comprehension—0
An Experimental Study of Deep Neural Network Models for Vietnamese Multiple-Choice Reading Comprehension—0
Bi-directional CognitiveThinking Network for Machine Reading Comprehension—0
A Deep Cascade Model for Multi-Document Reading Comprehension—0
Bi-directional Cognitive Thinking Network for Machine Reading Comprehension—0
Benchmarks for Pirá 2.0, a Reading Comprehension Dataset about the Ocean, the Brazilian Coast, and Climate Change—0
A New Entity Extraction Method Based on Machine Reading Comprehension—0
未登錄詞之向量表示法模型於中文機器閱讀理解之應用 (An OOV Word Embedding Framework for Chinese Machine Reading Comprehension) [In Chinese]—0
Comparison of Open-Source and Proprietary LLMs for Machine Reading Comprehension: A Practical Analysis for Industrial Applications—0
An End-to-End Dialogue State Tracking System with Machine Reading Comprehension and Wide & Deep Classification—0
A Vietnamese Dataset for Evaluating Machine Reading Comprehension—0
A Vietnamese Dataset for Evaluating Machine Reading Comprehension—0
Medical Knowledge Graph QA for Drug-Drug Interaction Prediction based on Multi-hop Machine Reading Comprehension—0
Addressing Semantic Drift in Generative Question Answering with Auxiliary Extraction—0
Data Augmentation for Biomedical Factoid Question Answering—0
Automatic Word Segmentation and Part-of-Speech Tagging of Ancient Chinese Based on BERT Model—0
An Effective Multi-Stage Approach For Question Answering—0
A Data-centric Framework for Improving Domain-specific Machine Reading Comprehension Datasets—0
A Unified Abstractive Model for Generating Question-Answer Pairs—0
An Attentive Sequence Model for Adverse Drug Event Extraction from Biomedical Text—0
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