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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 201–250 of 555 papers

TitleStatusHype
An MRC Framework for Semantic Role Labeling—0
Enhancing Answer Boundary Detection for Multilingual Machine Reading Comprehension—0
Improving Machine Reading Comprehension via Adversarial Training—0
Enhancing Pre-Trained Generative Language Models with Question Attended Span Extraction on Machine Reading Comprehension—0
Investigating a Benchmark for Training-set free Evaluation of Linguistic Capabilities in Machine Reading Comprehension—0
Enhancing Robustness of Retrieval-Augmented Language Models with In-Context Learning—0
Ensemble Learning-Based Approach for Improving Generalization Capability of Machine Reading Comprehension Systems—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
Improving Pre-Trained Multilingual Models with Vocabulary Expansion—0
ESTER: A Machine Reading Comprehension Dataset for Reasoning about Event Semantic Relations—0
Answer Generation through Unified Memories over Multiple Passages—0
Integrating Semantic Information into Sketchy Reading Module of Retro-Reader for Vietnamese Machine Reading Comprehension—0
Evaluating the Robustness of Machine Reading Comprehension Models to Low Resource Entity Renaming—0
Evaluation Metrics for Machine Reading Comprehension: Prerequisite Skills and Readability—0
Evaluation of Dataset Selection for Pre-Training and Fine-Tuning Transformer Language Models for Clinical Question Answering—0
Evaluation of Instruction-Following Ability for Large Language Models on Story-Ending Generation—0
EveMRC: A Two-stage Evidence Modeling For Multi-choice Machine Reading Comprehension—0
CSReader at SemEval-2018 Task 11: Multiple Choice Question Answering as Textual Entailment—0
Event Extraction as Machine Reading Comprehension—0
Building Dynamic Knowledge Graphs from Text using Machine Reading Comprehension—0
Answer Uncertainty and Unanswerability in Multiple-Choice Machine Reading Comprehension—0
Cross-Task Knowledge Transfer for Query-Based Text Summarization—0
A Survey on Measuring and Mitigating Reasoning Shortcuts in Machine Reading Comprehension—0
Exploring and Exploiting Multi-Granularity Representations for Machine Reading Comprehension—0
Explicit Utilization of General Knowledge in Machine Reading Comprehension—0
A Survey on Machine Reading Comprehension: Tasks, Evaluation Metrics and Benchmark Datasets—0
Cross-lingual Machine Reading Comprehension with Language Branch Knowledge Distillation—0
Feature-augmented Machine Reading Comprehension with Auxiliary Tasks—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
Feeding What You Need by Understanding What You Learned—0
Analysing the Effect of Masking Length Distribution of MLM: An Evaluation Framework and Case Study on Chinese MRC Datasets—0
A Survey on Machine Reading Comprehension Systems—0
ForceReader: a BERT-based Interactive Machine Reading Comprehension Model with Attention Separation—0
Cross-lingual and Cross-domain Evaluation of Machine Reading Comprehension with Squad and CALOR-Quest Corpora—0
FQuAD: French Question Answering Dataset—0
Challenges in Procedural Multimodal Machine Comprehension:A Novel Way To Benchmark—0
A Pairwise Probe for Understanding BERT Fine-Tuning on Machine Reading Comprehension—0
Enhancing lexical-based approach with external knowledge for Vietnamese multiple-choice machine reading comprehension—0
From Good to Best: Two-Stage Training for Cross-lingual Machine Reading Comprehension—0
Analyse automatique en cadres s\'emantiques pour l'apprentissage de mod\`eles de compr\'ehension de texte (Semantic Frame Parsing for training Machine Reading Comprehension models)—0
G4: Grounding-guided Goal-oriented Dialogues Generation with Multiple Documents—0
Cosmos QA: Machine Reading Comprehension with Contextual Commonsense Reasoning—0
GAAMA 2.0: An Integrated System that Answers Boolean and Extractive Questions—0
Correcting the Misuse: A Method for the Chinese Idiom Cloze Test—0
A Survey on Explainability in Machine Reading Comprehension—0
Adaptive Bi-directional Attention: Exploring Multi-Granularity Representations for Machine Reading Comprehension—0
Graph-Based Knowledge Integration for Question Answering over Dialogue—0
Graph-combined Coreference Resolution Methods on Conversational Machine Reading Comprehension with Pre-trained Language Model—0
Explicit Contextual Semantics for Text Comprehension—0
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