mlsanityData to 14 Oct 2026

Ask To The Point: Open-Domain Entity-Centric Question Generation

arXiv 2310.14126 ↗First posted 21 Oct 2023cs.CL cs.AIcited by 2

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Abstract (arXiv)

We introduce a new task called *entity-centric question generation* (ECQG), motivated by real-world applications such as topic-specific learning, assisted reading, and fact-checking. The task aims to generate questions from an entity perspective. To solve ECQG, we propose a coherent PLM-based framework GenCONE with two novel modules: content focusing and question verification. The content focusing module first identifies a focus as "what to ask" to form draft questions, and the question verification module refines the questions afterwards by verifying the answerability. We also construct a large-scale open-domain dataset from SQuAD to support this task. Our extensive experiments demonstrate that GenCONE significantly and consistently outperforms various baselines, and two modules are effective and complementary in generating high-quality questions.

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 29 of its 45 references that are in the map. First posted on arXiv 21 Oct 2023.

Builds on

29 of 45 references.

References · 29

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  2. 2020Retrieval-Augmented Generation for Knowledge-Intensive NLP Taskscited by 9,297
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  11. 2020CTRLsum: Towards Generic Controllable Text Summarizationcited by 98
  12. 2019Addressing Semantic Drift in Question Generation for Semi-Supervised Question Answeringcited by 63
17 more
  1. 2021Zero-shot Fact Verification by Claim Generationcited by 42
  2. 2022A Survey of Multi-task Learning in Natural Language Processing: Regarding Task Relatedness and Training Methodscited by 42
  3. 2020Asking Questions the Human Way: Scalable Question-Answer Generation from Text Corpuscited by 40
  4. 2021Controllable Neural Dialogue Summarization with Personal Named Entity Planningcited by 36
  5. 2022Educational Question Generation of Children Storybooks via Question Type Distribution Learning and Event-Centric Summarizationcited by 26
  6. 2021Improving Unsupervised Question Answering via Summarization-Informed Question Generationcited by 21
  7. 2019Interconnected Question Generation with Coreference Alignment and Conversation Flow Modelingcited by 20
  8. 2022Towards Process-Oriented, Modular, and Versatile Question Generation that Meets Educational Needscited by 19
  9. 2019Question-type Driven Question Generationcited by 16
  10. 2019Evaluating Rewards for Question Generation Modelscited by 15
  11. 2021Guiding Visual Question Generationcited by 14
  12. 2019Multi-Task Learning with Language Modeling for Question Generationcited by 10
  13. 2020Knowledge-enriched, Type-constrained and Grammar-guided Question Generation over Knowledge Basescited by 9
  14. 2019Review-based Question Generation with Adaptive Instance Transfer and Augmentationcited by 8
  15. 2022Entity-Conditioned Question Generation for Robust Attention Distribution in Neural Information Retrievalcited by 5
  16. 2021Generating Self-Contained and Summary-Centric Question Answer Pairs via Differentiable Reward Imitation Learningcited by 2
  17. 2022Enhancing Pre-trained Models with Text Structure Knowledge for Question Generationcited by 1

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Citing papers per year: 2024: 1; 2025: 1.

2 papers.

  1. 2024Certifying Knowledge Comprehension in LLMscited by 1
  2. 2025Writing Like the Best: Exemplar-Based Expository Text Generationcited by 0