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# Who cites «Fantastic Questions and Where to Find Them: FairytaleQA – An Authentic Dataset for Narrative Comprehension»

72 papers of our library cite it, newest first: found in their bibliographies, which we read ourselves. [← the card](https://md.mova.elamur.ai/free/en/docs/papers/xu-2022-fantastic-questions-where-find-them/)

1. [Construction and Analysis of Japanese Parent-Child Dialogic Reading Corpus for Conversational Agents](https://aclanthology.org/2026.lrec-1.213/) *— 2026 · Proceedings of the Fifteenth Language Resources and Evaluation Conference*
2. [Multi-Agent-as-Judge: Aligning LLM-Agent-Based Automated Evaluation with Multi-Dimensional Human Evaluation](https://aclanthology.org/2026.acl-long.790/) *— 2026 · Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
3. [ReproNLP 2026: A Third Replication of the Human Evaluation of a QAG System for Children''s Storybooks](https://aclanthology.org/2026.gem-main.85/) *— 2026 · Proceedings of the Fifth Workshop on Generation, Evaluation and Metrics (GEM)*
4. [Culturally Aware and Adapted NLP: A Taxonomy and a Survey of the State of the Art](https://aclanthology.org/2025.tacl-1.31/) *— 2025 · Transactions of the Association for Computational Linguistics*
5. [LLMs Are Biased Towards Output Formats! Systematically Evaluating and Mitigating Output Format Bias of LLMs](https://aclanthology.org/2025.naacl-long.15/) *— 2025 · Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)*
6. [PersianMCQ-Instruct: A Comprehensive Resource for Generating Multiple-Choice Questions in Persian](https://aclanthology.org/2025.loreslm-1.27/) *— 2025 · Proceedings of the First Workshop on Language Models for Low-Resource Languages*
7. [Persona-SQ: A Personalized Suggested Question Generation Framework For Real-world Documents](https://aclanthology.org/2025.naacl-demo.20/) *— 2025 · Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (System Demonstrations)*
8. [Prototypical Human-AI Collaboration Behaviors from LLM-Assisted Writing in the Wild](https://aclanthology.org/2025.emnlp-main.852/) *— 2025 · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing*
9. [The Essence of Contextual Understanding in Theory of Mind: A Study on Question Answering with Story Characters](https://aclanthology.org/2025.acl-long.1103/) *— 2025 · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
10. [Chain-of-Exemplar: Enhancing Distractor Generation for Multimodal Educational Question Generation](https://aclanthology.org/2024.acl-long.432/) *— 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
11. [FAC$^2$E: Better Understanding Large Language Model Capabilities by Dissociating Language and Cognition](https://aclanthology.org/2024.emnlp-main.734/) *— 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing*
12. [Fine-Grained Modeling of Narrative Context: A Coherence Perspective via Retrospective Questions](https://aclanthology.org/2024.acl-long.317/) *— 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
13. [Generative Interpretation: Toward Human-Like Evaluation for Educational Question-Answer Pair Generation](https://aclanthology.org/2024.findings-eacl.145/) *— 2024 · Findings of the Association for Computational Linguistics: EACL 2024*
14. [Instruction Pre-Training: Language Models are Supervised Multitask Learners](https://aclanthology.org/2024.emnlp-main.148/) *— 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing*
15. [Large language models for education: A survey and outlook](https://arxiv.org/abs/2403.18105) *— 2024*
16. [Multilingual Synopses of Movie Narratives: A Dataset for Vision-Language Story Understanding](https://aclanthology.org/2024.findings-emnlp.788/) *— 2024 · Findings of the Association for Computational Linguistics: EMNLP 2024*
17. [Once Upon a Replication: It is Humans'' Turn to Evaluate AI''s Understanding of Children''s Stories for QA Generation](https://aclanthology.org/2024.humeval-1.10/) *— 2024 · Proceedings of the Fourth Workshop on Human Evaluation of NLP Systems (HumEval) @ LREC-COLING 2024*
18. [Reading Subtext: Evaluating Large Language Models on Short Story Summarization with Writers](https://aclanthology.org/2024.tacl-1.71/) *— 2024 · Transactions of the Association for Computational Linguistics*
19. [SyllabusQA: A Course Logistics Question Answering Dataset](https://aclanthology.org/2024.acl-long.557/) *— 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
20. [Towards Cross-Tokenizer Distillation: the Universal Logit Distillation Loss for LLMs](https://arxiv.org/abs/2402.12030) *— 2024 · arXiv:2402.12030 · Transactions on Machine Learning Research, January 2025*
21. [大语言模型故事理解能力评价数据集(Benchmarking story comprehension ability of large language model)](https://aclanthology.org/2024.ccl-1.60/) *— 2024 · Proceedings of the 23rd Chinese National Conference on Computational Linguistics (Volume 1: Main Conference)*
22. [Are Fairy Tales Fair? Analyzing Gender Bias in Temporal Narrative Event Chains of Children's Fairy Tales](https://aclanthology.org/2023.acl-long.359/) *— 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
23. [Are Human Explanations Always Helpful? Towards Objective Evaluation of Human Natural Language Explanations](https://aclanthology.org/2023.acl-long.821/) *— 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
24. [Are NLP Models Good at Tracing Thoughts: An Overview of Narrative Understanding](https://aclanthology.org/2023.findings-emnlp.677/) *— 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023*
25. [Beyond Labels: Empowering Human Annotators with Natural Language Explanations through a Novel Active-Learning Architecture](https://aclanthology.org/2023.findings-emnlp.778/) *— 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023*
26. [Comparing Neural Question Generation Architectures for Reading Comprehension](https://aclanthology.org/2023.bea-1.47/) *— 2023 · Proceedings of the 18th Workshop on Innovative Use of NLP for Building Educational Applications (BEA 2023)*
27. [Cross-corpus Readability Compatibility Assessment for English Texts](https://arxiv.org/abs/2306.09704) *— 2023 · arXiv:2306.09704*
28. [FLASK: Fine-grained Language Model Evaluation based on Alignment Skill Sets](https://arxiv.org/abs/2307.10928) *— 2023 · arXiv:2307.10928*
29. [Improving Reading Comprehension Question Generation with Data Augmentation and Overgenerate-and-rank](https://aclanthology.org/2023.bea-1.22/) *— 2023 · Proceedings of the 18th Workshop on Innovative Use of NLP for Building Educational Applications (BEA 2023)*
30. [Learning to Filter Context for Retrieval-Augmented Generation](https://arxiv.org/abs/2311.08377) *— 2023 · arXiv:2311.08377*
31. [MultiQG-TI: Towards Question Generation from Multi-modal Sources](https://aclanthology.org/2023.bea-1.55/) *— 2023 · Proceedings of the 18th Workshop on Innovative Use of NLP for Building Educational Applications (BEA 2023)*
32. [PaniniQA: Enhancing Patient Education Through Interactive Question Answering](https://aclanthology.org/2023.tacl-1.86/) *— 2023 · Transactions of the Association for Computational Linguistics*
33. [Personality Understanding of Fictional Characters during Book Reading](https://aclanthology.org/2023.acl-long.826/) *— 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
34. [Selecting Better Samples from Pre-trained LLMs: A Case Study on Question Generation](https://aclanthology.org/2023.findings-acl.820/) *— 2023 · Findings of the Association for Computational Linguistics: ACL 2023*
35. [SkillQG: Learning to Generate Question for Reading Comprehension Assessment](https://aclanthology.org/2023.findings-acl.870/) *— 2023 · Findings of the Association for Computational Linguistics: ACL 2023*
36. [Towards Diverse and Effective Question-Answer Pair Generation from Children Storybooks](https://aclanthology.org/2023.findings-acl.380/) *— 2023 · Findings of the Association for Computational Linguistics: ACL 2023*
37. [Discord Questions: A Computational Approach To Diversity Analysis in News Coverage](https://aclanthology.org/2022.findings-emnlp.380/) *— 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022*
38. [GEMv2: Multilingual NLG Benchmarking in a Single Line of Code](https://aclanthology.org/2022.emnlp-demos.27/) *— 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing: System Demonstrations*
39. [It is AI''s Turn to Ask Humans a Question: Question-Answer Pair Generation for Children''s Story Books](https://md.mova.elamur.ai/free/en/docs/papers/yao-2022-it-is-ai-s-turn/) *— our card · 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
40. [MBTI Personality Prediction for Fictional Characters Using Movie Scripts](https://aclanthology.org/2022.findings-emnlp.500/) *— 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022*
41. [Narrative Why-Question Answering: A Review of Challenges and Datasets](https://aclanthology.org/2022.gem-1.48/) *— 2022 · Proceedings of the Second Workshop on Natural Language Generation, Evaluation, and Metrics (GEM)*
42. [TVShowGuess: Character Comprehension in Stories as Speaker Guessing](https://aclanthology.org/2022.naacl-main.317/) *— 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
43. ashok-2025-little-human-data-goes-long
44. berger-2026-generation-evaluation-resource-error-categorized
45. braga-2024-geracao-automatica-de-perguntas-em
46. chance-2025-will-prince-get-true-love
47. chen-2024-storysparkqa-expert-annotated-qa-pairs
48. ding-2024-sgcm-salience-guided-context-modeling
49. dutulescu-2026-orso-qgen-odds-ratio-steerable
50. gioffre-2026-indaqa2-large-italian-narrative-qa
51. hwang-2026-can-llms-estimate-cognitive-complexity
52. jang-2025-chatbot-help-patients-understand-their
53. jin-2024-select-high-quality-synthetic-qa
54. johnson-2025-ficsim-dataset-multi-faceted-semantic
55. kalbaliyev-2024-narrative-question-answering-skills
56. kao-2022-applying-information-extraction-storybook-question
57. kumar-2022-augmenting-ebooks-recommended-questions-contrastive
58. lee-2022-interactive-children-s-story-rewriting
59. lee-2023-story-co-telling-dialogue-generation
60. lee-2023-story-co-telling-dialogue-generation-2023-rocling-1-2
61. leite-2025-advancing-question-generation-joint-narrative
62. li-2025-crossqg-improving-difficulty-controllable-question
63. ma-2025-automatic-generation-inference-making-questions
64. naeem-2025-eduadapt-question-answer-benchmark-dataset
65. preda-2026-automated-extraction-answer-candidates-question
66. tsai-2024-pg-story-taxonomy-dataset-evaluation
67. wang-2024-interpreting-answers-yes-no-questions
68. wang-2025-beyond-textual-generating-coherent-visual
69. yoon-2023-diversity-enhanced-narrative-question-generation
70. zhang-2024-interpreting-themes-educational-stories
71. zhao-2023-parrot-zero-shot-narrative-reading
72. zhou-2025-d-score-document-centric-segmentation
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