Generating Natural Language Question-Answer Pairs from a Knowledge Graph Using a RNN Based Question Generation Model

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Multiple Choice Question Generation Utilizing An Ontology

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A Survey of Cross-Modal Visual Content Generation

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Addressing Semantic Drift in Question Generation for Semi-Supervised Question AnsweringPreprint

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Thematic Question Generation over Knowledge Bases

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Analysis of ChatGPT as a Question-Answering Tool

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AttractionDetailsQA: An Attraction Details Focused on Chinese Question Answering Dataset

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Learning to Generate Question by Asking Question: A Primal-Dual Approach with Uncommon Word Generation

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LEMON: A Knowledge-Enhanced, Type-Constrained, and Grammar-Guided Model for Question Generation Over Knowledge Graphs

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A Comprehensive Study on a Deep-Learning-Based Electrocardiography Analysis for Estimating the Apnea-Hypopnea Index

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Towards building an affect-aware dialogue agent with deep neural networks

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PROTEGE: Prompt-based Diverse Question Generation from Web Articles

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IQ-VQA: Intelligent Visual Question Answering

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GameOfThronesQA: Answer-Aware Question-Answer Pairs for TV Series

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Towards a Better Metric for Evaluating Question Generation SystemsPreprint

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Let's Ask Again: Refine Network for Automatic Question GenerationPreprint

Nema, P., Mohankumar, A. K., Khapra, M. M., Srinivasan, B. V., & Ravindran, B. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1909.05355 · Cited by 4 · see citing works

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Descriptor: Open-Domain Long-Form Context-Aware Question-Answering Dataset (DragonVerseQA)

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Semantic Understanding of Natural Language Stories for Near Human Question Answering

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WikiOmnia: filtration and evaluation of the generated QA corpus on the whole Russian Wikipedia

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Generating Multiple Choice Questions from Scientific Literature via Large Language Models

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Named Entity-based Question-Answering Pair Generator

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Learning to Ask: Question-based Sequential Bayesian Product SearchPreprint

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A Study on Various Approaches Towards Non-Factoid Question Answering Systems

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Automation of Question-Answer Generation

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Graph and Question Interaction Aware Graph2Seq Model for Knowledge Base Question Generation

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Generating and Answering Simple and Complex Questions from Text and from Knowledge Graphs

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Mixing It Up: Inducing Empathy and Politeness using Multiple Behaviour-aware Generators for Conversational Systems

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Attentional Seq2Seq Model for Arabic Opinion Question Generation

Ouahrani, L., & Bennouar, D. (2025) · Lecture notes in networks and systems · doi:10.1007/978-3-031-82112-7_9 · Cited by 1 · see citing works

HouseOfTheDragonQA: Open-Domain Long-form Context-Aware QA Pairs for TV Series

Lahiri, A. K., & Hu, Q. (2024) · IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT) · doi:10.1109/wi-iat62293.2024.00028 · Cited by 1 · see citing works

Transferring Human Tutor's Style to Pedagogical Agent: A Possible Way by Leveraging Variety of Artificial Intelligence Achievements

Feng, X., Guo, X., Qiu, L., & Shi, R. (2018) · IEEE International Conference on Teaching, Assessment, and Learning for Engineering · doi:10.1109/tale.2018.8615413 · Cited by 1 · see citing works

Text Generation from Triple via Generative Adversarial Nets

Chen, X., Lin, D., & Cao, D. (2019) · Communications in computer and information science · doi:10.1007/978-981-15-1377-0_44 · Cited by 1 · see citing works

Knowledge-enriched, Type-constrained and Grammar-guided Question Generation over Knowledge BasesPreprint

Bi, S., Cheng, X., Li, Y.-F., Wang, Y., & Qi, G. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2010.03157 · Cited by 1 · see citing works

Scalable Micro-planned Generation of Discourse from Structured Data

Laha, A., Jain, P., Mishra, A., & Sankaranarayanan, K. (2019) · Computational Linguistics · doi:10.1162/coli_a_00363

Natural Answer Generation with QA Pairs Using Sequence to Sequence Model

Liu, M., Liu, J., & Ren, H. (2018) · Lecture notes in electrical engineering · doi:10.1007/978-981-13-1328-8_42

Populating the knowledge base of a conversational agent

Rodrigues, H. P., Coheur, L., & Nyberg, E. (2019) · ACM Symposium on Applied Computing · doi:10.1145/3297280.3297380

Separating the Signal from the Noise: Predicting the Correct Entities in Named-Entity Linking

Perkins, D. (2020) · Uppsala University Publications (Uppsala University)

Questions Generation for Reading Comprehension Using Coherence Relations

Anamika, Pathak, V., Shrivastava, V., & Panday, A. (2021) · Algorithms for intelligent systems · doi:10.1007/978-981-15-6707-0_6

How Well Do You Know Your Audience? Reader-aware Question Generation.Preprint

Stewart, I., & Mihalcea, R. F. (2021) · arXiv (Cornell University)

Calculating Question Similarity is Enough: A New Method for KBQA TasksPreprint

Zhao, H., Yuan, S., Leng, J., Pan, X., Wang, G., Wu, L., & Tang, J. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2111.07658

Generating Complex Questions from Knowledge Graphs with Query Graphs

Wang, Z. (2022) · IEEE International Conference on Information, Communication and Networks (ICICN) · doi:10.1109/icicn56848.2022.10006514

Automatic question generation from natural language texts

Cao, Z. (2022) · doi:10.32657/10356/164625

Entity Level QA Pairs Dataset for Sentiment Analysis

Lahiri, A. K., & Hu, Q. (2022) · IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT) · doi:10.1109/wi-iat55865.2022.00046

A Research on Attraction Details Question-answer Pair Generation based on Gate Attention Unit

Huang, W., Jin, F., & Chang, Q. (2023) · International Conference on Electronic Communication and Artificial Intelligence (ICECAI) · doi:10.1109/icecai58670.2023.10176653

Controllable and One-to-many Generate QA pairs from Contexts for Semi-Supervised Question Answering

Zhang, X., Huang, J., & Fang, Y. (2023) · International Conference on Big Data & Artificial Intelligence & Software Engineering (ICBASE) · doi:10.1109/icbase59196.2023.10303233

Enabling Dynamic Interactions between Natural Language and Structured Knowledg Bases

Elsahar, H. (2019) · doi:10.70675/4944f792z8529z4f8azb2cdzac4385d2705d

QA-GNN: Reasoning with Language Models and Knowledge Graphs for Question Answering

Yasunaga, M., Ren, H., Bosselut, A., Liang, P., & Leskovec, J. (2021) · Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT) · doi:10.18653/v1/2021.naacl-main.45 · Cited by 620 · see citing works

Generating and Answering Simple and Complex Questions from Text and from Knowledge Graphs

Han, K., & Gardent, C. (2023) · International Joint Conference on Natural Language Processing and Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics (IJCNLP-AACL) · doi:10.18653/v1/2023.ijcnlp-main.19 · Cited by 1 · see citing works

RNN Based Natural Language Sentence Generation from a Knowledge Graph and Keyword Sequence

Kwon, S., Noh, Y., Choi, S.-J., & Park, S. (2018) · Annual Conference on Human and Language Technology

D-RAG: Differentiable Retrieval-Augmented Generation for Knowledge Graph Question Answering

Gao, G., Li, Z., Yuan, C., Li, J., Jianzhuo, W., Zhang, Y., Jin, X., Li, B., & Hu, W. (2025) · Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.18653/v1/2025.emnlp-main.1793 · Cited by 6 · see citing works

Conversational Question Answering over Knowledge Graphs with Transformer and Graph Attention Networks

Kacupaj, E., Plepi, J., Singh, K., Thakkar, H., Lehmann, J., & Maleshkova, M. (2021) · Conference of the European Chapter of the Association for Computational Linguistics · doi:10.18653/v1/2021.eacl-main.72 · Cited by 55 · see citing works