---
title: "Who cites TellMeWhy: A Dataset for Answering Why-Questions…"
description: "The papers of the Elamur Research library that cite «TellMeWhy: A Dataset for Answering Why-Questions in Narratives», found in their bibliographies."
canonical: "https://research.elamur.ai/free/en/papers/lal-2021-tellmewhy-dataset-answering-why-questions/cited-by/"
---
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[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [TellMeWhy: A Dataset for Answering Why-Questions…](https://md.research.elamur.ai/free/en/papers/lal-2021-tellmewhy-dataset-answering-why-questions/) / cited by

# 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.research.elamur.ai/free/en/papers/lal-2021-tellmewhy-dataset-answering-why-questions/)

1. [Can Stories Help LLMs Reason? Curating Information Space Through Narrative](https://aclanthology.org/2025.analogyangle-1.8/) *— 2025 · Proceedings of the 2nd Workshop on Analogical Abstraction in Cognition, Perception, and Language (Analogy-Angle II)*
2. [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*
3. [From Curiosity to Clarity : Exploring the Impact of Consecutive Why-Questions](https://aclanthology.org/2025.findings-naacl.202/) *— 2025 · Findings of the Association for Computational Linguistics: NAACL 2025*
4. [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*
5. [Quriosity: Analyzing Human Questioning Behavior and Causal Inquiry through Curiosity-Driven Queries](https://aclanthology.org/2025.findings-ijcnlp.32/) *— 2025 · Proceedings of the 14th International Joint Conference on Natural Language Processing and the 4th Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics*
6. [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)*
7. [Think Both Ways: Teacher-Student Bidirectional Reasoning Enhances MCQ Generation and Distractor Quality](https://aclanthology.org/2025.findings-acl.432/) *— 2025 · Findings of the Association for Computational Linguistics: ACL 2025*
8. [Towards Evaluation of Language Models with Skill Dimensions: A Case Study on Narrative Question Answering](https://aclanthology.org/2025.starsem-1.34/) *— 2025 · Proceedings of the 14th Joint Conference on Lexical and Computational Semantics (*SEM 2025)*
9. [A Critical Review of Causal Reasoning Benchmarks for Large Language Models](https://arxiv.org/abs/2407.08029) *— 2024 · arXiv:2407.08029*
10. [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*
11. [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)*
12. [On Narrative Question Answering Skills](https://aclanthology.org/2024.naacl-short.73/) *— 2024 · Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 2: Short Papers)*
13. [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*
14. [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*
15. [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)*
16. [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*
17. [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)*
18. [Benchmarks for Automated Commonsense Reasoning: A Survey](https://arxiv.org/abs/2302.04752) *— 2023 · arXiv:2302.04752*
19. [CLadder: Assessing Causal Reasoning in Language Models](https://arxiv.org/abs/2312.04350) *— 2023 · arXiv:2312.04350*
20. [Diversity Enhanced Narrative Question Generation for Storybooks](https://aclanthology.org/2023.emnlp-main.31/) *— 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing*
21. [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)*
22. [Natural Language Reasoning, A Survey](https://arxiv.org/abs/2303.14725) *— 2023 · arXiv:2303.14725*
23. [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*
24. [CausalQA: A Benchmark for Causal Question Answering](https://aclanthology.org/2022.coling-1.291/) *— 2022 · Proceedings of the 29th International Conference on Computational Linguistics*
25. [Fantastic Questions and Where to Find Them: FairytaleQA – An Authentic Dataset for Narrative Comprehension](https://md.research.elamur.ai/free/en/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)*
26. [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*
27. [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*
28. [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)*
29. [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*
30. [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*