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Machine Reading Comprehension

36 papers with code · Natural Language Processing

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A Framework for Evaluation of Machine Reading Comprehension Gold Standards

10 Mar 2020schlevik/dataset-analysis

Machine Reading Comprehension (MRC) is the task of answering a question over a paragraph of text.

MACHINE READING COMPREHENSION

0
10 Mar 2020

Asking Questions the Human Way: Scalable Question-Answer Generation from Text Corpus

27 Jan 2020bangliu/ACS-QG

In this paper, we propose Answer-Clue-Style-aware Question Generation (ACS-QG), which aims at automatically generating high-quality and diverse question-answer pairs from unlabeled text corpus at scale by imitating the way a human asks questions.

CHATBOT MACHINE READING COMPREHENSION QUESTION ANSWERING QUESTION GENERATION

14
27 Jan 2020

Coreference Resolution as Query-based Span Prediction

5 Nov 2019ShannonAI/CorefQA

In this paper, we present an accurate and extensible approach for the coreference resolution task.

COREFERENCE RESOLUTION DATA AUGMENTATION MACHINE READING COMPREHENSION

12
05 Nov 2019

A Unified MRC Framework for Named Entity Recognition

25 Oct 2019ShannonAI/mrc-for-flat-nested-ner

Instead of treating the task of NER as a sequence labeling problem, we propose to formulate it as a machine reading comprehension (MRC) task.

 SOTA for Nested Named Entity Recognition on ACE 2004 (using extra training data)

CHINESE NAMED ENTITY RECOGNITION ENTITY EXTRACTION MACHINE READING COMPREHENSION NESTED MENTION RECOGNITION NESTED NAMED ENTITY RECOGNITION

44
25 Oct 2019

BiPaR: A Bilingual Parallel Dataset for Multilingual and Cross-lingual Reading Comprehension on Novels

IJCNLP 2019 sharejing/BiPaR

We analyze BiPaR in depth and find that BiPaR offers good diversification in prefixes of questions, answer types and relationships between questions and passages.

COREFERENCE RESOLUTION MACHINE READING COMPREHENSION

18
11 Oct 2019

Semantics-aware BERT for Language Understanding

5 Sep 2019cooelf/SemBERT

The latest work on language representations carefully integrates contextualized features into language model training, which enables a series of success especially in various machine reading comprehension and natural language inference tasks.

LANGUAGE MODELLING MACHINE READING COMPREHENSION NATURAL LANGUAGE INFERENCE QUESTION ANSWERING SEMANTIC ROLE LABELING WORD EMBEDDINGS

88
05 Sep 2019

Cross-Lingual Machine Reading Comprehension

IJCNLP 2019 ymcui/Cross-Lingual-MRC

In this paper, we propose Cross-Lingual Machine Reading Comprehension (CLMRC) task for the languages other than English.

MACHINE READING COMPREHENSION

43
01 Sep 2019

Interactive Machine Comprehension with Information Seeking Agents

27 Aug 2019xingdi-eric-yuan/imrc_public

Existing machine reading comprehension (MRC) models do not scale effectively to real-world applications like web-level information retrieval and question answering (QA).

DECISION MAKING INFORMATION RETRIEVAL MACHINE READING COMPREHENSION QUESTION ANSWERING

11
27 Aug 2019

SG-Net: Syntax-Guided Machine Reading Comprehension

14 Aug 2019cooelf/SG-Net

In detail, for self-attention network (SAN) sponsored Transformer-based encoder, we introduce syntactic dependency of interest (SDOI) design into the SAN to form an SDOI-SAN with syntax-guided self-attention.

LANGUAGE MODELLING MACHINE READING COMPREHENSION QUESTION ANSWERING

13
14 Aug 2019

GraphFlow: Exploiting Conversation Flow with Graph Neural Networks for Conversational Machine Comprehension

31 Jul 2019hugochan/GraphFlow

In addition, visualization experiments show that our proposed model can better mimic the human reasoning process for conversational MRC compared to existing models.

MACHINE READING COMPREHENSION

2
31 Jul 2019