SOTAVerified

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 451–500 of 664 papers

TitleStatusHype
A Survey of Approaches to Automatic Question Generation:from 2019 to Early 2021—0
A Survey on Neural Question Generation: Methods, Applications, and Prospects—0
A Syntactic Approach to Domain-Specific Automatic Question Generation—0
A System For Robot Concept Learning Through Situated Dialogue—0
A Unified Abstractive Model for Generating Question-Answer Pairs—0
A Unified Query-based Generative Model for Question Generation and Question Answering—0
AutoEQA: Auto-Encoding Questions for Extractive Question Answering—0
Auto FAQ Generation—0
AutoGEEval: A Multimodal and Automated Framework for Geospatial Code Generation on GEE with Large Language Models—0
Automated Question Generation for Science Tests in Arabic Language Using NLP Techniques—0
Automated Question Generation on Tabular Data for Conversational Data Exploration—0
Automatic Answerability Evaluation for Question Generation—0
Automatic Follow-up Question Generation for Asynchronous Interviews—0
Automatic Generation of Grounded Visual Questions—0
Automatic Generation of Multiple-Choice Questions—0
Automatic Learning Assistant in Telugu—0
Automatic question generation based on sentence structure analysis using machine learning approach—0
Automatic question generation for propositional logical equivalences—0
Automatic Question Generation in Multimedia-Based Learning—0
Automatic Question Generation using Relative Pronouns and Adverbs—0
Automatic True/False Question Generation for Educational Purpose—0
Automating question generation from educational text—0
Automating Reading Comprehension by Generating Question and Answer Pairs—0
A Weak Supervision Approach for Predicting Difficulty of Technical Interview Questions—0
A Well-Composed Text is Half Done! Composition Sampling for Diverse Conditional Generation—0
A Well-Composed Text is Half Done! Semantic Composition Sampling for Diverse Conditional Generation—0
What BERT Sees: Cross-Modal Transfer for Visual Question Generation—0
BERT for Question Generation—0
Best-k Search Algorithm for Neural Text Generation—0
Better Distractions: Transformer-based Distractor Generation and Multiple Choice Question Filtering—0
Bridging The Gap: Entailment Fused-T5 for Open-retrieval Conversational Machine Reading Comprehension—0
Bringing personalized learning into computer-aided question generation—0
Calculating Question Similarity is Enough: A New Method for KBQA Tasks—0
Calibrating Sequence likelihood Improves Conditional Language Generation—0
Can Question Generation Debias Question Answering Models? A Case Study on Question–Context Lexical Overlap—0
Chat-based Person Retrieval via Dialogue-Refined Cross-Modal Alignment—0
ChatPRCS: A Personalized Support System for English Reading Comprehension based on ChatGPT—0
Choose Your Own Adventure: Interactive E-Books to Improve Word Knowledge and Comprehension Skills—0
ColdGANs: Taming Language GANs with Cautious Sampling Strategies—0
Competence-based Question Generation—0
Compressed and Smooth Latent Space for Text Diffusion Modeling—0
Conditional Generation with a Question-Answering Blueprint—0
ConQuest: Contextual Question Paraphrasing through Answer-Aware Synthetic Question Generation—0
Consecutive Question Generation via Dynamic Multitask Learning—0
Consecutive Question Generation with Multitask Joint Reranking and Dynamic Rationale Search—0
Controlling the Specificity of Clarification Question Generation—0
Conversational Multi-Hop Reasoning with Neural Commonsense Knowledge and Symbolic Logic Rules—0
ConVQG: Contrastive Visual Question Generation with Multimodal Guidance—0
Cooperative Self-training of Machine Reading Comprehension—0
Cooperative Semi-Supervised Transfer Learning of Machine Reading Comprehension—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