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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 251–300 of 664 papers

TitleStatusHype
KG-QAGen: A Knowledge-Graph-Based Framework for Systematic Question Generation and Long-Context LLM EvaluationCode0
Generating Self-Contained and Summary-Centric Question Answer Pairs via Differentiable Reward Imitation LearningCode0
Improving Socratic Question Generation using Data Augmentation and Preference OptimizationCode0
Learning to Reuse Distractors to support Multiple Choice Question Generation in EducationCode0
Multi-hop Reading Comprehension through Question Decomposition and RescoringCode0
Towards Verifiable Generation: A Benchmark for Knowledge-aware Language Model AttributionCode0
Generating Questions and Multiple-Choice Answers using Semantic Analysis of Texts—0
Generating Natural Questions from Images for Multimodal Assistants—0
Generating Natural Language Question-Answer Pairs from a Knowledge Graph Using a RNN Based Question Generation Model—0
A Survey of Approaches to Automatic Question Generation:from 2019 to Early 2021—0
Generating Highly Relevant Questions—0
Generating Followup Questions for Interpretable Multi-hop Question Answering—0
ColdGANs: Taming Language GANs with Cautious Sampling Strategies—0
Assumption Questioning: Latent Copying and Reward Exploitation in Question Generation—0
A New Dialogue Response Generation Agent for Large Language Models by Asking Questions to Detect User's Intentions—0
Generating Answer Candidates for Quizzes and Answer-Aware Question Generators—0
From text to multimodal: a survey of adversarial example generation in question answering systems—0
Follow-up Question Generation For Enhanced Patient-Provider Conversations—0
FOLLOWUPQG: Towards Information-Seeking Follow-up Question Generation—0
Few-Shot Visual Question Generation: A Novel Task and Benchmark Datasets—0
Few-shot Question Generation for Personalized Feedback in Intelligent Tutoring Systems—0
Fantastic Questions and Where to Find Them: FairytaleQA – An Authentic Dataset for Narrative Comprehension—0
Ask to Understand: Question Generation for Multi-hop Question Answering—0
An Automated Multiple-Choice Question Generation Using Natural Language Processing Techniques—0
Choose Your Own Adventure: Interactive E-Books to Improve Word Knowledge and Comprehension Skills—0
Extrapolating Multilingual Understanding Models as Multilingual Generators—0
Extending Interactive Science Exhibits into the Classroom using Anthropomorphized Chatbots and Bloom's Taxonomy—0
ChatPRCS: A Personalized Support System for English Reading Comprehension based on ChatGPT—0
Extended Answer and Uncertainty Aware Neural Question Generation—0
Chat-based Person Retrieval via Dialogue-Refined Cross-Modal Alignment—0
Ask to Learn: A Study on Curiosity-driven Question Generation—0
An ASP-based Approach to Answering Natural Language Questions for Texts—0
Exploring Input Representation Granularity for Generating Questions Satisfying Question-Answer Congruence—0
Exploring Answer Information Methods for Question Generation with Transformers—0
Explicit Alignment and Many-to-many Entailment Based Reasoning for Conversational Machine Reading—0
Expanding Chatbot Knowledge in Customer Service: Context-Aware Similar Question Generation Using Large Language Models—0
Event Extraction as Machine Reading Comprehension—0
Ask Question with Double Hints: Visual Question Generation with Answer-awareness and Region-reference—0
An AI-based Solution for Enhancing Delivery of Digital Learning for Future Teachers—0
A Feasibility Study of Answer-Unaware Question Generation for Education—0
A Consolidated Dataset for Knowledge-based Question Generation using Predicate Mapping of Linked Data—0
Evaluation of Question Generation Needs More References—0
Evaluation Metrics of Language Generation Models for Synthetic Traffic Generation Tasks—0
Evaluation methodologies in Automatic Question Generation 2013-2018—0
Evaluating the Fitness of Ontologies for the Task of Question Generation—0
Can Question Generation Debias Question Answering Models? A Case Study on Question–Context Lexical Overlap—0
Evaluating for Diversity in Question Generation over Text—0
Calibrating Sequence likelihood Improves Conditional Language Generation—0
AskQE: Question Answering as Automatic Evaluation for Machine Translation—0
Calculating Question Similarity is Enough: A New Method for KBQA Tasks—0
Show:102550
← PrevPage 6 of 14Next →
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