Machine Reading Comprehension
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Greatest papers with code
DuReader: a Chinese Machine Reading Comprehension Dataset from Real-world Applications
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.
Pre-Training with Whole Word Masking for Chinese BERT
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.
SOTA for Chinese Sentence Pair Classification on BQ (F1 metric )
DOCUMENT CLASSIFICATION LANGUAGE MODELLING MACHINE READING COMPREHENSION NAMED ENTITY RECOGNITION NATURAL LANGUAGE INFERENCE SENTIMENT ANALYSIS
CLUE: A Chinese Language Understanding Evaluation Benchmark
We introduce CLUE, a Chinese Language Understanding Evaluation benchmark.
Sogou Machine Reading Comprehension Toolkit
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.
DRCD: a Chinese Machine Reading Comprehension Dataset
In this paper, we introduce DRCD (Delta Reading Comprehension Dataset), an open domain traditional Chinese machine reading comprehension (MRC) dataset.
MS MARCO: A Human Generated MAchine Reading COmprehension Dataset
The size of the dataset and the fact that the questions are derived from real user search queries distinguishes MS MARCO from other well-known publicly available datasets for machine reading comprehension and question-answering.
A Span-Extraction Dataset for Chinese Machine Reading Comprehension
IJCNLP 2019
• ymcui/cmrc2018
• 
Machine Reading Comprehension (MRC) has become enormously popular recently and has attracted a lot of attention.
Dual Ask-Answer Network for Machine Reading Comprehension
• hanxiao/daanet
•
The task of question answering or question generation aims to infer an answer or a question when given the counterpart based on context.
MACHINE READING COMPREHENSION QUESTION ANSWERING QUESTION GENERATION
Stochastic Answer Networks for SQuAD 2.0
• kevinduh/san_mrc
• 
This paper presents an extension of the Stochastic Answer Network (SAN), one of the state-of-the-art machine reading comprehension models, to be able to judge whether a question is unanswerable or not.
Multi-task Learning with Sample Re-weighting for Machine Reading Comprehension
NAACL 2019
• kevinduh/san_mrc
•
We propose a multi-task learning framework to learn a joint Machine Reading Comprehension (MRC) model that can be applied to a wide range of MRC tasks in different domains.
MACHINE READING COMPREHENSION MACHINE TRANSLATION MULTI-TASK LEARNING QUESTION ANSWERING