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Found 7 papers, 0 papers with code
Learning to Generate Questions by Recovering Answer-containing Sentences
We evaluate our method against existing ones in terms of the quality of generated questions as well as the fine-tuned MRC model accuracy after training on the data synthetically generated by our method.
Ranked #3 on
Question Generation
on SQuAD1.1
(using extra training data)
NeurQuRI: Neural Question Requirement Inspector for Answerability Prediction in Machine Reading Comprehension
Real-world question answering systems often retrieve potentially relevant documents to a given question through a keyword search, followed by a machine reading comprehension (MRC) step to find the exact answer from them.
ASGen: Answer-containing Sentence Generation to Pre-Train Question Generator for Scale-up Data in Question Answering
We evaluate the question generation capability of our method by comparing the BLEU score with existing methods and test our method by fine-tuning the MRC model on the downstream MRC data after training on synthetic data.
Cut to the Chase: A Context Zoom-in Network for Reading Comprehension
In recent years many deep neural networks have been proposed to solve Reading Comprehension (RC) tasks.
Ranked #4 on
Question Answering
on NarrativeQA
MemoReader: Large-Scale Reading Comprehension through Neural Memory Controller
Machine reading comprehension helps machines learn to utilize most of the human knowledge written in the form of text.
Ranked #27 on
Question Answering
on TriviaQA
(using extra training data)
A Multi-Stage Memory Augmented Neural Network for Machine Reading Comprehension
Reading Comprehension (RC) of text is one of the fundamental tasks in natural language processing.
Ranked #69 on
Question Answering
on SQuAD1.1
