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 601–625 of 664 papers

Title	Date	Tasks	Status
NIPS Conversational Intelligence Challenge 2017 Winner System: Skill-based Conversational Agent with Supervised Dialog Manager	Aug 1, 2018	Goal-Oriented DialogGoal-Oriented Dialogue Systems	CodeCode Available
Rethinking the Agreement in Human Evaluation Tasks	Aug 1, 2018	Dialogue GenerationQuestion Generation	—Unverified
Difficulty Controllable Generation of Reading Comprehension Questions	Jul 10, 2018	Question GenerationQuestion-Generation	—Unverified
Sequential Copying Networks	Jul 6, 2018	DecoderQuestion Generation	CodeCode Available
Neural Models for Key Phrase Extraction and Question Generation	Jul 1, 2018	Question AnsweringQuestion Generation	—Unverified
Automatic Question Generation using Relative Pronouns and Adverbs	Jul 1, 2018	DescriptiveDialogue Generation	—Unverified
Learning to Automatically Generate Fill-In-The-Blank Quizzes	Jun 12, 2018	BIG-bench Machine LearningDeep Learning	—Unverified
Interactive Visual Grounding of Referring Expressions for Human-Robot Interaction	Jun 11, 2018	Question GenerationQuestion-Generation	—Unverified
Learn from Your Neighbor: Learning Multi-modal Mappings from Sparse Annotations	Jun 8, 2018	DiversityMulti-Label Classification	—Unverified
A Semantic Role-based Approach to Open-Domain Automatic Question Generation	Jun 1, 2018	Dependency ParsingQuestion Generation	—Unverified
Learning to Collaborate for Question Answering and Asking	Jun 1, 2018	Answer SelectionGenerative Adversarial Network	—Unverified
Leveraging Context Information for Natural Question Generation	Jun 1, 2018	PositionQuestion Generation	CodeCode Available
Self-Training for Jointly Learning to Ask and Answer Questions	Jun 1, 2018	Data AugmentationQuestion Answering	—Unverified
Soft Layer-Specific Multi-Task Summarization with Entailment and Question Generation	May 28, 2018	Abstractive Text SummarizationDecoder	—Unverified
Harvesting Paragraph-Level Question-Answer Pairs from Wikipedia	May 15, 2018	ArticlesQuestion Generation	CodeCode Available
Learning to Ask Questions in Open-domain Conversational Systems with Typed Decoders	May 13, 2018	DecoderQuestion Generation	CodeCode Available
Customized Image Narrative Generation via Interactive Visual Question Generation and Answering	Apr 27, 2018	DiversityImage Description	—Unverified
Two can play this Game: Visual Dialog with Discriminative Question Generation and Answering	Mar 29, 2018	Image CaptioningQuestion Answering	—Unverified
Automating Reading Comprehension by Generating Question and Answer Pairs	Mar 7, 2018	Answer GenerationQuestion Generation	—Unverified
Zero-Shot Question Generation from Knowledge Graphs for Unseen Predicates and Entity Types	Feb 19, 2018	DecoderKnowledge Graphs	CodeCode Available
Topic-Based Question Generation	Jan 1, 2018	ChatbotDescriptive	—Unverified
A Syntactic Approach to Domain-Specific Automatic Question Generation	Dec 28, 2017	Question AnsweringQuestion Generation	—Unverified
Asking the Difficult Questions: Goal-Oriented Visual Question Generation via Intermediate Rewards	Nov 21, 2017	Deep Reinforcement LearningInformativeness	—Unverified
iVQA: Inverse Visual Question Answering	Oct 10, 2017	Question AnsweringQuestion Generation	—Unverified
Visual Question Generation as Dual Task of Visual Question Answering	Sep 21, 2017	Question AnsweringQuestion 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