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# Who cites «ParaShoot: A Hebrew Question Answering Dataset»

12 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/ud-2021-keren-parashoot-hebrew-question-answering-dataset/)

1. [A Dataset for Metaphor Detection in Early Medieval Hebrew Poetry](https://md.mova.elamur.ai/free/en/docs/papers/eacl-2024-toker-dataset-metaphor-detection-early-medieval/) *— our card · 2024 · Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics (Volume 2: Short Papers)*
2. [HeSum: a Novel Dataset for Abstractive Text Summarization in Hebrew](https://md.mova.elamur.ai/free/en/docs/papers/findings-2024-argaman-hesum-novel-dataset-abstractive-text/) *— our card · 2024 · Findings of the Association for Computational Linguistics: ACL 2024*
3. [Mevaker: Conclusion Extraction and Allocation Resources for the Hebrew Language](https://md.mova.elamur.ai/free/en/docs/papers/langstream-2024-shalumov-mevaker-conclusion-extraction-allocation-resources/) *— our card · 2024 · arXiv:2403.09719*
4. [RoQLlama: A Lightweight Romanian Adapted Language Model](https://aclanthology.org/2024.findings-emnlp.261/) *— 2024 · Findings of the Association for Computational Linguistics: EMNLP 2024*
5. [Explicit Morphological Knowledge Improves Pre-training of Language Models for Hebrew](https://md.mova.elamur.ai/free/en/docs/papers/langstream-2023-gueta-explicit-morphological-knowledge-improves-pre/) *— our card · 2023 · arXiv:2311.00658*
6. [HeQ: a Large and Diverse Hebrew Reading Comprehension Benchmark](https://md.mova.elamur.ai/free/en/docs/papers/findings-2023-cohen-heq-large-diverse-hebrew-reading/) *— our card · 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023*
7. [HeRo: RoBERTa and Longformer Hebrew Language Models](https://md.mova.elamur.ai/free/en/docs/papers/langstream-2023-shalumov-hero-roberta-longformer-hebrew-language/) *— our card · 2023 · arXiv:2304.11077*
8. [Introducing DictaLM -- A Large Generative Language Model for Modern Hebrew](https://md.mova.elamur.ai/free/en/docs/papers/langstream-2023-shmidman-introducing-dictalm-large-generative-language/) *— our card · 2023 · arXiv:2309.14568*
9. [Multilingual Sequence-to-Sequence Models for Hebrew NLP](https://md.mova.elamur.ai/free/en/docs/papers/findings-2023-eyal-multilingual-sequence-sequence-models-hebrew/) *— our card · 2023 · Findings of the Association for Computational Linguistics: ACL 2023*
10. [Question-Answering in a Low-resourced Language: Benchmark Dataset and Models for Tigrinya](https://aclanthology.org/2023.acl-long.661/) *— 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
11. [Natural Questions in Icelandic](https://aclanthology.org/2022.lrec-1.477/) *— 2022 · Proceedings of the Thirteenth Language Resources and Evaluation Conference*
12. masad-2023-automatic-translation-span-prediction-datasets
- [← previous Who cites «Annotation guidelines of UD and SUD treebanks for spoken corpora: A proposal»](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/ud-2021-kahane-annotation-guidelines-ud-sud-treebanks/)
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