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# Who cites «TellMeWhy: A Dataset for Answering Why-Questions in Narratives»

30 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/lal-2021-tellmewhy-dataset-answering-why-questions/)

1. [Culturally-Nuanced Story Generation for Reasoning in Low-Resource Languages: The Case of Javanese and Sundanese](https://arxiv.org/abs/2502.12932) *— 2025 · arXiv:2502.12932*
2. [NarratEX Dataset: Explaining the Dominant Narratives in News Texts](https://aclanthology.org/2025.findings-emnlp.1112/) *— 2025 · Findings of the Association for Computational Linguistics: EMNLP 2025*
3. [SemEval 2025 Task 10: Multilingual Characterization and Extraction of Narratives from Online News](https://aclanthology.org/2025.semeval-1.331/) *— 2025 · Proceedings of the 19th International Workshop on Semantic Evaluation (SemEval-2025)*
4. [A Critical Review of Causal Reasoning Benchmarks for Large Language Models](https://arxiv.org/abs/2407.08029) *— 2024 · arXiv:2407.08029*
5. [CaT-Bench: Benchmarking Language Model Understanding of Causal and Temporal Dependencies in Plans](https://aclanthology.org/2024.emnlp-main.1077/) *— 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing*
6. [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)*
7. [SAGA: A Participant-specific Examination of Story Alternatives and Goal Applicability for a Deeper Understanding of Complex Events](https://aclanthology.org/2024.findings-acl.910/) *— 2024 · Findings of the Association for Computational Linguistics: ACL 2024*
8. [Tailoring with Targeted Precision: Edit-Based Agents for Open-Domain Procedure Customization](https://aclanthology.org/2024.findings-acl.921/) *— 2024 · Findings of the Association for Computational Linguistics: ACL 2024*
9. [ALERT: Adapt Language Models to Reasoning Tasks](https://aclanthology.org/2023.acl-long.60/) *— 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
10. [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*
11. [Automatic Evaluation of Generative Models with Instruction Tuning](https://aclanthology.org/2023.gem-1.4/) *— 2023 · Proceedings of the Third Workshop on Natural Language Generation, Evaluation, and Metrics (GEM)*
12. [Benchmarks for Automated Commonsense Reasoning: A Survey](https://arxiv.org/abs/2302.04752) *— 2023 · arXiv:2302.04752*
13. [CLadder: Assessing Causal Reasoning in Language Models](https://arxiv.org/abs/2312.04350) *— 2023 · arXiv:2312.04350*
14. [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)*
15. [Natural Language Reasoning, A Survey](https://arxiv.org/abs/2303.14725) *— 2023 · arXiv:2303.14725*
16. [NovaCOMET: Open Commonsense Foundation Models with Symbolic Knowledge Distillation](https://aclanthology.org/2023.findings-emnlp.80/) *— 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023*
17. [CausalQA: A Benchmark for Causal Question Answering](https://aclanthology.org/2022.coling-1.291/) *— 2022 · Proceedings of the 29th International Conference on Computational Linguistics*
18. [Fantastic Questions and Where to Find Them: FairytaleQA – An Authentic Dataset for Narrative Comprehension](https://md.mova.elamur.ai/free/en/docs/papers/xu-2022-fantastic-questions-where-find-them/) *— our card · 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
19. [How about Time? Probing a Multilingual Language Model for Temporal Relations](https://aclanthology.org/2022.coling-1.283/) *— 2022 · Proceedings of the 29th International Conference on Computational Linguistics*
20. [Inferring Implicit Relations in Complex Questions with Language Models](https://aclanthology.org/2022.findings-emnlp.188/) *— 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022*
21. [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)*
22. [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*
23. [Using Commonsense Knowledge to Answer Why-Questions](https://aclanthology.org/2022.emnlp-main.79/) *— 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing*
24. ceraolo-2025-quriosity-analyzing-human-questioning-behavior
25. javadi-2025-can-stories-help-llms-reason
26. kalbaliyev-2024-narrative-question-answering-skills
27. kalbaliyev-2025-evaluation-language-models-skill-dimensions
28. qiu-2025-think-both-ways-teacher-student
29. son-2025-curiosity-clarity-exploring-impact-consecutive
30. yoon-2023-diversity-enhanced-narrative-question-generation
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