Question Generation

The goal of Question Generation is to generate a valid and fluent question according to a given passage and the target answer. Question Generation can be used in many scenarios, such as automatic tutoring systems, improving the performance of Question Answering models and enabling chatbots to lead a conversation.

Source: Generating Highly Relevant Questions

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 626–650 of 664 papers

Title	Date	Tasks	Status
A Unified Query-based Generative Model for Question Generation and Question Answering	Sep 4, 2017	DecoderQuestion Answering	—Unverified
Multiple Choice Question Generation Utilizing An Ontology	Sep 1, 2017	Distractor GenerationMultiple-choice	—Unverified
Identifying Where to Focus in Reading Comprehension for Neural Question Generation	Sep 1, 2017	Dependency ParsingMachine Translation	—Unverified
Question Generation for Language Learning: From ensuring texts are read to supporting learning	Sep 1, 2017	Decision MakingForm	—Unverified
Question Generation for Question Answering	Sep 1, 2017	ChatbotQuestion Answering	—Unverified
Learning to Disambiguate by Asking Discriminative Questions	Aug 9, 2017	BenchmarkingImage Captioning	—Unverified
Crowdsourcing Multiple Choice Science Questions	Jul 19, 2017	DiversityMultiple-choice	—Unverified
Domain Specific Automatic Question Generation from Text	Jul 1, 2017	Dependency ParsingQuestion Generation	—Unverified
Neural Models for Key Phrase Detection and Question Generation	Jun 14, 2017	Question AnsweringQuestion Generation	—Unverified
Question Answering and Question Generation as Dual Tasks	Jun 7, 2017	Question AnsweringQuestion Generation	—Unverified
A Joint Model for Question Answering and Question Generation	Jun 5, 2017	Question AnsweringQuestion Generation	—Unverified
Machine Comprehension by Text-to-Text Neural Question Generation	May 4, 2017	Question AnsweringQuestion Generation	CodeCode Available
The Forgettable-Watcher Model for Video Question Answering	May 3, 2017	modelQuestion Answering	—Unverified
Creativity: Generating Diverse Questions using Variational Autoencoders	Apr 11, 2017	Question GenerationQuestion-Generation	—Unverified
Generating Natural Language Question-Answer Pairs from a Knowledge Graph Using a RNN Based Question Generation Model	Apr 1, 2017	Knowledge GraphsQuestion Answering	—Unverified
Automatic Generation of Grounded Visual Questions	Dec 20, 2016	DiversityQuestion Generation	—Unverified
Probabilistic Prototype Model for Serendipitous Property Mining	Dec 1, 2016	modelQuestion Generation	—Unverified
Generating Questions and Multiple-Choice Answers using Semantic Analysis of Texts	Dec 1, 2016	coreference-resolutionCoreference Resolution	—Unverified
Question Generation from a Knowledge Base with Web Exploration	Oct 12, 2016	Natural QuestionsQuestion Generation	—Unverified
QGASP: a Framework for Question Generation Based on Different Levels of Linguistic Information	Sep 1, 2016	Question GenerationQuestion-Generation	—Unverified
Infusing NLU into Automatic Question Generation	Sep 1, 2016	Question GenerationQuestion-Generation	—Unverified
Good Automatic Authentication Question Generation	Sep 1, 2016	Common Sense ReasoningDependency Parsing	—Unverified
Selecting Domain-Specific Concepts for Question Generation With Lightly-Supervised Methods	Sep 1, 2016	Open Information ExtractionQuestion Generation	—Unverified
Supersense Embeddings: A Unified Model for Supersense Interpretation, Prediction, and Utilization	Aug 1, 2016	Dependency ParsingDocument Classification	—Unverified
Language Muse: Automated Linguistic Activity Generation for English Language Learners	Aug 1, 2016	Question Generation	—Unverified

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All datasets SQuAD1.1 COCO Visual Question Answering (VQA) real images 1.0 open ended GrailQA-Compositional GrailQA-IID GrailQA-Zero-Shot FairytaleQA WeiboPolls Natural Questions SQuAD TriviaQA Visual Question Generation

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	ERNIE-GENLARGE (beam size=5)	BLEU-4	25.41	—	Unverified
2	BART (TextBox 2.0)	BLEU-4	25.08	—	Unverified
3	ProphetNet + ASGen	BLEU-4	24.44	—	Unverified
4	UniLMv2	BLEU-4	24.43	—	Unverified
5	ProphetNet + syn. mask + localness	BLEU-4	24.37	—	Unverified
6	ProphetNet	BLEU-4	23.91	—	Unverified
7	UniLM + ASGen	BLEU-4	23.7	—	Unverified
8	UniLM	BLEU-4	22.78	—	Unverified
9	BERTSQG	BLEU-4	22.17	—	Unverified
10	Selector & NQG++	BLEU-4	15.87	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	MDN	BLEU-1	65.1	—	Unverified
2	coco-Caption [[Karpathy and Li2014]]	BLEU-1	62.5	—	Unverified
3	Max(Yang,2015)	BLEU-1	59.4	—	Unverified
4	Sample(Yang,2015)	BLEU-1	38.8	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	FactJointGT	METEOR	36.21	—	Unverified
2	JointGT	METEOR	36.08	—	Unverified
3	FactT5B	METEOR	35.72	—	Unverified
4	T5B	METEOR	35.64	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	FactT5B	BLEU	46.1	—	Unverified
2	JointGT	BLEU	45.95	—	Unverified
3	T5B	BLEU	44.51	—	Unverified
4	FactJointGT	BLEU	43.61	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	JointGT	METEOR	37.69	—	Unverified
2	FactJointGT	METEOR	37.55	—	Unverified
3	FactT5B	METEOR	37.39	—	Unverified
4	T5B	METEOR	37.35	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	BART fine-tuned on FairytaleQA	ROUGE-L	0.53	—	Unverified
2	BART fine-tuned on NarrativeQA and FairytaleQA	ROUGE-L	0.52	—	Unverified
3	BART fine-tuned on NarrativeQA	ROUGE-L	0.44	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	UniPoll	ROUGE-1	49.6	—	Unverified
2	T5	ROUGE-1	44.46	—	Unverified
3	Dual Dec	ROUGE-1	38.24	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Info-HCVAE	QAE	37.18	—	Unverified
2	HCVAE	QAE	31.45	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Info-HCVAE	QAE	71.18	—	Unverified
2	HCVAE	QAE	69.46	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Info-HCVAE	QAE	35.45	—	Unverified
2	HCVAE	QAE	30.2	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	MDN	BLEU-1	36	—	Unverified