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# Who cites «Ellipsis Resolution as Question Answering: An Evaluation»

8 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/eacl-2021-aralikatte-ellipsis-resolution-as-question-answering/)

1. [Low-Hallucination and Efficient Coreference Resolution with LLMs](https://aclanthology.org/2025.findings-emnlp.934/) *— 2025 · Findings of the Association for Computational Linguistics: EMNLP 2025*
2. [Discursive Socratic Questioning: Evaluating the Faithfulness of Language Models'' Understanding of Discourse Relations](https://aclanthology.org/2024.acl-long.341/) *— 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
3. [Design Choices for Crowdsourcing Implicit Discourse Relations: Revealing the Biases Introduced by Task Design](https://aclanthology.org/2023.tacl-1.57/) *— 2023*
4. [Discourse Analysis via Questions and Answers: Parsing Dependency Structures of Questions Under Discussion](https://md.mova.elamur.ai/free/en/docs/papers/ko-2023-discourse-analysis-questions-answers-parsing/) *— our card · 2023 · Findings of the Association for Computational Linguistics: ACL 2023*
5. [Ellipsis-Dependent Reasoning: a New Challenge for Large Language Models](https://aclanthology.org/2023.acl-short.4/) *— 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)*
6. [We Understand Elliptical Sentences, and Language Models should Too: A New Dataset for Studying Ellipsis and its Interaction with Thematic Fit](https://md.mova.elamur.ai/free/en/docs/papers/acl-2023-testa-we-understand-elliptical-sentences-language/) *— our card · 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
7. [Verb Phrase Anaphora:Do(ing) so with Heuristics](https://aclanthology.org/2022.icon-main.13/) *— 2022 · Proceedings of the 19th International Conference on Natural Language Processing (ICON)*
8. li-2026-bediscover-benchmark-discourse-understanding-era
- [← previous Who cites «English Machine Reading Comprehension Datasets: A Survey»](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/dzendzik-2021-english-machine-reading-comprehension-datasets/)
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