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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

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Showing 251–300 of 664 papers

TitleStatusHype
基于迭代信息传递和滑动窗口注意力的问题生成模型研究(Question Generation Model Based on Iterative Message Passing and Sliding Windows Hierarchical Attention)—0
Generating Natural Language Question-Answer Pairs from a Knowledge Graph Using a RNN Based Question Generation Model—0
Generating Natural Questions from Images for Multimodal Assistants—0
Generating Questions and Multiple-Choice Answers using Semantic Analysis of Texts—0
Deep Bayesian Network for Visual Question Generation—0
Decision-Theoretic Question Generation for Situated Reference Resolution: An Empirical Study and Computational Model—0
Davidsonian Scene Graph: Improving Reliability in Fine-grained Evaluation for Text-to-Image Generation—0
Automatic Generation of Multiple-Choice Questions—0
A Reinforcement Learning Framework for Natural Question Generation using Bi-discriminators—0
Data Augmentation with Hierarchical SQL-to-Question Generation for Cross-domain Text-to-SQL Parsing—0
Automatic Generation of Grounded Visual Questions—0
Data Augmentation for Biomedical Factoid Question Answering—0
Automatic Follow-up Question Generation for Asynchronous Interviews—0
AGenT Zero: Zero-shot Automatic Multiple-Choice Question Generation for Skill Assessments—0
JEFF - Just Another EFFicient Reading Comprehension Test Generation—0
基于Graph Transformer的知识库问题生成(Question Generation from Knowledge Base with Graph Transformer)—0
Keep it Consistent: Topic-Aware Storytelling from an Image Stream via Iterative Multi-agent Communication—0
Cycle-Consistency for Robust Visual Question Answering—0
Customized Image Narrative Generation via Interactive Visual Question Generation and Answering—0
Automatic Answerability Evaluation for Question Generation—0
Crowdsourcing Multiple Choice Science Questions—0
Cross-lingual Transfer for Automatic Question Generation by Learning Interrogative Structures in Target Languages—0
A Question Type Driven and Copy Loss Enhanced Frameworkfor Answer-Agnostic Neural Question Generation—0
CAVEN: An Embodied Conversational Agent for Efficient Audio-Visual Navigation in Noisy Environments—0
Cross-Examiner: Evaluating Consistency of Large Language Model-Generated Explanations—0
Applying Information Extraction to Storybook Question and Answer Generation—0
Creativity: Generating Diverse Questions using Variational Autoencoders—0
Automated Question Generation on Tabular Data for Conversational Data Exploration—0
INVIGORATE: Interactive Visual Grounding and Grasping in Clutter—0
ISEEQ: Information Seeking Question Generation using Dynamic Meta-Information Retrieval and Knowledge Graphs—0
Covering Uncommon Ground: Gap-Focused Question Generation for Answer Assessment—0
Co-Trained Retriever-Generator Framework for Question Generation in Earnings Calls—0
Automated Question Generation for Science Tests in Arabic Language Using NLP Techniques—0
Corpus-informed Retrieval Augmented Generation of Clarifying Questions—0
Improving Question Answering Model Robustness with Synthetic Adversarial Data Generation—0
CopyBERT: A Unified Approach to Question Generation with Self-Attention—0
Investigating Answerability of LLMs for Long-Form Question Answering—0
Cooperative Semi-Supervised Transfer Learning of Machine Reading Comprehension—0
Answer-guided and Semantic Coherent Question Generation in Open-domain Conversation—0
Improving Neural Question Generation using World Knowledge—0
Cooperative Self-training of Machine Reading Comprehension—0
A Free Lunch in Generating Datasets: Building a VQG and VQA System with Attention and Humans in the Loop—0
Improving Controllability of Educational Question Generation by Keyword Provision—0
Improving Biomedical Information Retrieval with Neural Retrievers—0
idT5: Indonesian Version of Multilingual T5 Transformer—0
I Do Not Understand What I Cannot Define: Automatic Question Generation With Pedagogically-Driven Content Selection—0
Improving Question Generation with Sentence-level Semantic Matching and Answer Position Inferring—0
Improving Question Generation With to the Point Context—0
ConVQG: Contrastive Visual Question Generation with Multimodal Guidance—0
AutoGEEval: A Multimodal and Automated Framework for Geospatial Code Generation on GEE with Large Language Models—0
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All datasetsSQuAD1.1COCO Visual Question Answering (VQA) real images 1.0 open endedGrailQA-CompositionalGrailQA-IIDGrailQA-Zero-ShotFairytaleQAWeiboPollsNatural QuestionsSQuADTriviaQAVisual Question Generation

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ERNIE-GENLARGE (beam size=5)BLEU-425.41—Unverified
2BART (TextBox 2.0)BLEU-425.08—Unverified
3ProphetNet + ASGenBLEU-424.44—Unverified
4UniLMv2BLEU-424.43—Unverified
5ProphetNet + syn. mask + localnessBLEU-424.37—Unverified
6ProphetNetBLEU-423.91—Unverified
7UniLM + ASGenBLEU-423.7—Unverified
8UniLMBLEU-422.78—Unverified
9BERTSQGBLEU-422.17—Unverified
10Selector & NQG++BLEU-415.87—Unverified
#ModelMetricClaimedVerifiedStatus
1MDNBLEU-165.1—Unverified
2coco-Caption [[Karpathy and Li2014]]BLEU-162.5—Unverified
3Max(Yang,2015)BLEU-159.4—Unverified
4Sample(Yang,2015)BLEU-138.8—Unverified
#ModelMetricClaimedVerifiedStatus
1FactJointGTMETEOR36.21—Unverified
2JointGTMETEOR36.08—Unverified
3FactT5BMETEOR35.72—Unverified
4T5BMETEOR35.64—Unverified
#ModelMetricClaimedVerifiedStatus
1FactT5BBLEU46.1—Unverified
2JointGTBLEU45.95—Unverified
3T5BBLEU44.51—Unverified
4FactJointGTBLEU43.61—Unverified
#ModelMetricClaimedVerifiedStatus
1JointGTMETEOR37.69—Unverified
2FactJointGTMETEOR37.55—Unverified
3FactT5BMETEOR37.39—Unverified
4T5BMETEOR37.35—Unverified
#ModelMetricClaimedVerifiedStatus
1BART fine-tuned on FairytaleQAROUGE-L0.53—Unverified
2BART fine-tuned on NarrativeQA and FairytaleQAROUGE-L0.52—Unverified
3BART fine-tuned on NarrativeQAROUGE-L0.44—Unverified
#ModelMetricClaimedVerifiedStatus
1UniPollROUGE-149.6—Unverified
2T5ROUGE-144.46—Unverified
3Dual DecROUGE-138.24—Unverified
#ModelMetricClaimedVerifiedStatus
1Info-HCVAEQAE37.18—Unverified
2HCVAEQAE31.45—Unverified
#ModelMetricClaimedVerifiedStatus
1Info-HCVAEQAE71.18—Unverified
2HCVAEQAE69.46—Unverified
#ModelMetricClaimedVerifiedStatus
1Info-HCVAEQAE35.45—Unverified
2HCVAEQAE30.2—Unverified
#ModelMetricClaimedVerifiedStatus
1MDNBLEU-136—Unverified