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 576–600 of 664 papers

Title	Date	Tasks	Status
Question Generation using a Scratchpad Encoder	May 1, 2019	DecoderQuestion Generation	—Unverified
Information Maximizing Visual Question Generation	Mar 27, 2019	ClusteringQuestion Generation	—Unverified
Evaluating Rewards for Question Generation Models	Feb 28, 2019	Machine TranslationPolicy Gradient Methods	CodeCode Available
Learning to Generate Questions by Learning What not to Generate	Feb 27, 2019	Multi-Task LearningQuestion Answering	—Unverified
Cycle-Consistency for Robust Visual Question Answering	Feb 15, 2019	Question AnsweringQuestion Generation	—Unverified
Automatic Opinion Question Generation	Nov 1, 2018	Community Question AnsweringQuestion Answering	CodeCode Available
Evaluation methodologies in Automatic Question Generation 2013-2018	Nov 1, 2018	Question GenerationQuestion-Generation	—Unverified
Textual Entailment based Question Generation	Nov 1, 2018	Dependency ParsingNatural Language Inference	—Unverified
Answer-focused and Position-aware Neural Question Generation	Oct 1, 2018	Machine Reading ComprehensionPosition	—Unverified
Visual Curiosity: Learning to Ask Questions to Learn Visual Recognition	Oct 1, 2018	Question GenerationQuestion-Generation	—Unverified
Uncovering Code-Mixed Challenges: A Framework for Linguistically Driven Question Generation and Neural Based Question Answering	Oct 1, 2018	Question AnsweringQuestion Generation	—Unverified
Multimodal Differential Network for Visual Question Generation	Oct 1, 2018	Image CaptioningNatural Questions	—Unverified
Assumption Questioning: Latent Copying and Reward Exploitation in Question Generation	Sep 27, 2018	Inductive BiasMachine Translation	—Unverified
Knowledge Based Machine Reading Comprehension	Sep 12, 2018	Machine Reading ComprehensionQuestion Answering	—Unverified
Neural Generation of Diverse Questions using Answer Focus, Contextual and Linguistic Features	Sep 7, 2018	coreference-resolutionCoreference Resolution	—Unverified
Dual Ask-Answer Network for Machine Reading Comprehension	Sep 6, 2018	Machine Reading ComprehensionQuestion Answering	CodeCode Available
Goal-Oriented Visual Question Generation via Intermediate Rewards	Sep 1, 2018	Deep Reinforcement LearningInformativeness	—Unverified
Towards a Better Metric for Evaluating Question Generation Systems	Aug 30, 2018	Knowledge GraphsQuestion Generation	CodeCode Available
Development and Evaluation of a Personalized Computer-aided Question Generation for English Learners to Improve Proficiency and Correct Mistakes	Aug 29, 2018	Multiple-choiceQuestion Generation	—Unverified
Bringing personalized learning into computer-aided question generation	Aug 29, 2018	Question GenerationQuestion-Generation	—Unverified
Question Generation from SQL Queries Improves Neural Semantic Parsing	Aug 20, 2018	Question GenerationQuestion-Generation	—Unverified
Putting the Horse Before the Cart:A Generator-Evaluator Framework for Question Generation from Text	Aug 15, 2018	Question GenerationQuestion-Generation	—Unverified
Multimodal Differential Network for Visual Question Generation	Aug 12, 2018	Natural QuestionsQuestion Generation	CodeCode Available
Visual Question Generation for Class Acquisition of Unknown Objects	Aug 6, 2018	Question GenerationQuestion-Generation	CodeCode Available
A Reinforcement Learning Framework for Natural Question Generation using Bi-discriminators	Aug 1, 2018	AttributeNatural Questions	—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