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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 401–450 of 555 papers

TitleStatusHype
ASGen: Answer-containing Sentence Generation to Pre-Train Question Generator for Scale-up Data in Question Answering—0
Ask to Learn: A Study on Curiosity-driven Question Generation—0
Aspect-based Sentiment Analysis as Machine Reading Comprehension—0
Assessing the Benchmarking Capacity of Machine Reading Comprehension Datasets—0
A Study of the Tasks and Models in Machine Reading Comprehension—0
A Study on Contextualized Language Modeling for Machine Reading Comprehension—0
A Survey on Explainability in Machine Reading Comprehension—0
A Survey on Machine Reading Comprehension Systems—0
A Survey on Machine Reading Comprehension: Tasks, Evaluation Metrics and Benchmark Datasets—0
A Survey on Measuring and Mitigating Reasoning Shortcuts in Machine Reading Comprehension—0
A Survey on Neural Machine Reading Comprehension—0
Attention-based Aspect Reasoning for Knowledge Base Question Answering on Clinical Notes—0
Attention-Guided Answer Distillation for Machine Reading Comprehension—0
Audio-Oriented Multimodal Machine Comprehension: Task, Dataset and Model—0
A Unified Abstractive Model for Generating Question-Answer Pairs—0
Automatic Word Segmentation and Part-of-Speech Tagging of Ancient Chinese Based on BERT Model—0
A Vietnamese Dataset for Evaluating Machine Reading Comprehension—0
A Vietnamese Dataset for Evaluating Machine Reading Comprehension—0
Comparison of Open-Source and Proprietary LLMs for Machine Reading Comprehension: A Practical Analysis for Industrial Applications—0
Benchmarks for Pirá 2.0, a Reading Comprehension Dataset about the Ocean, the Brazilian Coast, and Climate Change—0
Bi-directional Cognitive Thinking Network for Machine Reading Comprehension—0
Bi-directional CognitiveThinking Network for Machine Reading Comprehension—0
Biomedical Question Answering: A Survey of Approaches and Challenges—0
BLCU-NLP at COIN-Shared Task1: Stagewise Fine-tuning BERT for Commonsense Inference in Everyday Narrations—0
Bridging Information-Seeking Human Gaze and Machine Reading Comprehension—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
CalibreNet: Calibration Networks for Multilingual Sequence 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
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
ChemistryQA: A Complex Question Answering Dataset from Chemistry—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
Clozer: Adaptable Data Augmentation for Cloze-style Reading Comprehension—0
Clozer”:" Adaptable Data Augmentation for Cloze-style Reading Comprehension—0
CLUF: a Neural Model for Second Language Acquisition Modeling—0
Collecting high-quality adversarial data for machine reading comprehension tasks with humans and models in the loop—0
Composing Answer from Multi-spans for Reading Comprehension—0
Context Modeling with Evidence Filter for Multiple Choice Question Answering—0
Context-Paraphrase Enhanced Commonsense Question Answering—0
Continual Domain Adaptation for Machine Reading Comprehension—0
Continual Machine Reading Comprehension via Uncertainty-aware Fixed Memory and Adversarial Domain Adaptation—0
Controlling Risk of Web Question Answering—0
Conversational Machine Comprehension: a Literature Review—0
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