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Machine Reading Comprehension

36 papers with code ยท Natural Language Processing

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TREC CAsT 2019: The Conversational Assistance Track Overview

30 Mar 2020

A common theme through the runs is the use of BERT-based neural reranking methods.

LEARNING-TO-RANK MACHINE READING COMPREHENSION

GenNet : Reading Comprehension with Multiple Choice Questions using Generation and Selection model

3 Mar 2020

Multiple-choice machine reading comprehension is difficult task as its required machines to select the correct option from a set of candidate or possible options using the given passage and question. Reading Comprehension with Multiple Choice Questions task, required a human (or machine) to read a given passage, question pair and select the best one option from n given options.

MACHINE READING COMPREHENSION

Multi-task Learning with Multi-head Attention for Multi-choice Reading Comprehension

26 Feb 2020

Multiple-choice Machine Reading Comprehension (MRC) is an important and challenging Natural Language Understanding (NLU) task, in which a machine must choose the answer to a question from a set of choices, with the question placed in context of text passages or dialog.

MACHINE READING COMPREHENSION MULTI-TASK LEARNING

FQuAD: French Question Answering Dataset

14 Feb 2020

FQuAD is French Native Reading Comprehension dataset that consists of 25, 000+ questions on a set of Wikipedia articles.

LANGUAGE MODELLING MACHINE READING COMPREHENSION QUESTION ANSWERING

Retrospective Reader for Machine Reading Comprehension

27 Jan 2020

Inspired by how humans solve reading comprehension questions, we proposed a retrospective reader (Retro-Reader) that integrates two stages of reading and verification strategies: 1) sketchy reading that briefly investigates the overall interactions of passage and question, and yield an initial judgment; 2) intensive reading that verifies the answer and gives the final prediction.

MACHINE READING COMPREHENSION

Dual Multi-head Co-attention for Multi-choice Reading Comprehension

26 Jan 2020

Multi-choice Machine Reading Comprehension (MRC) requires model to decide the correct answer from a set of answer options when given a passage and a question.

LANGUAGE MODELLING MACHINE READING COMPREHENSION

A Study of the Tasks and Models in Machine Reading Comprehension

23 Jan 2020

To provide a survey on the existing tasks and models in Machine Reading Comprehension (MRC), this report reviews: 1) the dataset collection and performance evaluation of some representative simple-reasoning and complex-reasoning MRC tasks; 2) the architecture designs, attention mechanisms, and performance-boosting approaches for developing neural-network-based MRC models; 3) some recently proposed transfer learning approaches to incorporating text-style knowledge contained in external corpora into the neural networks of MRC models; 4) some recently proposed knowledge base encoding approaches to incorporating graph-style knowledge contained in external knowledge bases into the neural networks of MRC models.

MACHINE READING COMPREHENSION TRANSFER LEARNING

A Pilot Study on Multiple Choice Machine Reading Comprehension for Vietnamese Texts

16 Jan 2020

In this paper, we introduce ViMMRC, a challenging machine comprehension corpus with multiple-choice questions, intended for research on the machine comprehension of Vietnamese text.

MACHINE READING COMPREHENSION

A BERT based Sentiment Analysis and Key Entity Detection Approach for Online Financial Texts

14 Jan 2020

Aiming at the issue, we propose a sentiment analysis and key entity detection approach based on BERT, which is applied in online financial text mining and public opinion analysis in social media.

MACHINE READING COMPREHENSION NAMED ENTITY RECOGNITION SENTIMENT ANALYSIS

A Survey on Machine Reading Comprehension Systems

6 Jan 2020

We illustrate the recent trends in this field based on 124 reviewed papers from 2016 to 2018.

MACHINE READING COMPREHENSION