Machine Reading Comprehension

115 papers with code • 2 benchmarks • 37 datasets

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

Greatest papers with code

DuReader: a Chinese Machine Reading Comprehension Dataset from Real-world Applications

PaddlePaddle/models WS 2018

Experiments show that human performance is well above current state-of-the-art baseline systems, leaving plenty of room for the community to make improvements.

Machine Reading Comprehension

Pre-Training with Whole Word Masking for Chinese BERT

ymcui/Chinese-BERT-wwm 19 Jun 2019

In this technical report, we adapt whole word masking in Chinese text, that masking the whole word instead of masking Chinese characters, which could bring another challenge in Masked Language Model (MLM) pre-training task.

Document Classification Document-level +6

CLUE: A Chinese Language Understanding Evaluation Benchmark

CLUEbenchmark/CLUE COLING 2020

The advent of natural language understanding (NLU) benchmarks for English, such as GLUE and SuperGLUE allows new NLU models to be evaluated across a diverse set of tasks.

General Classification Language understanding +3

DuReader_robust: A Chinese Dataset Towards Evaluating Robustness and Generalization of Machine Reading Comprehension in Real-World Applications

PaddlePaddle/Research 23 Apr 2020

Machine reading comprehension (MRC) is a crucial task in natural language processing and has achieved remarkable advancements.

Machine Reading Comprehension

Knowledge Aware Conversation Generation with Explainable Reasoning over Augmented Graphs

PaddlePaddle/Research IJCNLP 2019

Two types of knowledge, triples from knowledge graphs and texts from documents, have been studied for knowledge aware open-domain conversation generation, in which graph paths can narrow down vertex candidates for knowledge selection decision, and texts can provide rich information for response generation.

Knowledge Graphs Machine Reading Comprehension

Sogou Machine Reading Comprehension Toolkit

sogou/SMRCToolkit 28 Mar 2019

In this paper, we present a Sogou Machine Reading Comprehension (SMRC) toolkit that can be used to provide the fast and efficient development of modern machine comprehension models, including both published models and original prototypes.

Machine Reading Comprehension

A Unified MRC Framework for Named Entity Recognition

ShannonAI/mrc-for-flat-nested-ner ACL 2020

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

Ranked #2 on Named Entity Recognition on ACE 2005 (using extra training data)

Chinese Named Entity Recognition Entity Extraction using GAN +4

A Span-Extraction Dataset for Chinese Machine Reading Comprehension

ymcui/cmrc2018 IJCNLP 2019

Machine Reading Comprehension (MRC) has become enormously popular recently and has attracted a lot of attention.

Machine Reading Comprehension