[Mova](https://md.mova.elamur.ai/free/en/) · [this page in HTML](https://mova.elamur.ai/free/en/docs/papers/cited-by/aclbulk-2019-tsarfaty-what-s-wrong-hebrew-nlp/) [home](https://md.mova.elamur.ai/free/en/) / [docs](https://md.mova.elamur.ai/free/en/docs/) / [papers](https://md.mova.elamur.ai/free/en/docs/papers/) / [cited-by](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/) / Who cites «What's Wrong with Hebrew NLP? And How to Make it Right» # Who cites «What's Wrong with Hebrew NLP? And How to Make it Right» 20 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/aclbulk-2019-tsarfaty-what-s-wrong-hebrew-nlp/) 1. [MTQE.en-he: Machine Translation Quality Estimation for English-Hebrew](https://aclanthology.org/2026.loreslm-1.48/) *— 2026 · Proceedings of the Second Workshop on Language Models for Low-Resource Languages (LoResLM 2026)* 2. [Vocab Diet: Reshaping the Vocabulary of LLMs via Vector Arithmetic](https://aclanthology.org/2026.findings-acl.1618/) *— 2026 · Findings of the Association for Computational Linguistics: ACL 2026* 3. [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* 4. [MRL Parsing Without Tears: The Case of Hebrew](https://md.mova.elamur.ai/free/en/docs/papers/findings-2024-shmidman-mrl-parsing-without-tears-case/) *— our card · 2024 · Findings of the Association for Computational Linguistics: ACL 2024* 5. [Do Pretrained Contextual Language Models Distinguish between Hebrew Homograph Analyses?](https://md.mova.elamur.ai/free/en/docs/papers/eacl-2023-shmidman-do-pretrained-contextual-language-models/) *— our card · 2023 · Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics* 6. [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* 7. [HeGeL: A Novel Dataset for Geo-Location from Hebrew Text](https://md.mova.elamur.ai/free/en/docs/papers/findings-2023-argaman-hegel-novel-dataset-geo-location/) *— our card · 2023 · Findings of the Association for Computational Linguistics: ACL 2023* 8. [The Truth, The Whole Truth, and Nothing but the Truth: A New Benchmark Dataset for Hebrew Text Credibility Assessment](https://md.mova.elamur.ai/free/en/docs/papers/findings-2023-hagag-truth-whole-truth-nothing-but/) *— our card · 2023* 9. [Toward a Period-Specific Optimized Neural Network for OCR Error Correction of Historical Hebrew Texts](https://md.mova.elamur.ai/free/en/docs/papers/hbo-2023-suissa-toward-period-specific-optimized-neural/) *— our card · 2023 · arXiv:2307.16213* 10. [Introducing BEREL: BERT Embeddings for Rabbinic-Encoded Language](https://md.mova.elamur.ai/free/en/docs/papers/hbo-2022-shmidman-introducing-berel-bert-embeddings-rabbinic/) *— our card · 2022 · arXiv:2208.01875* 11. [Restoring Hebrew Diacritics Without a Dictionary](https://md.mova.elamur.ai/free/en/docs/papers/findings-2022-gershuni-restoring-hebrew-diacritics-without-dictionary/) *— our card · 2022 · Findings of the Association for Computational Linguistics: NAACL 2022* 12. [AlephBERT:A Hebrew Large Pre-Trained Language Model to Start-off your Hebrew NLP Application With](https://md.mova.elamur.ai/free/en/docs/papers/langstream-2021-seker-alephbert-hebrew-large-pre-trained/) *— our card · 2021 · arXiv:2104.04052* 13. [NLP in the DH pipeline: Transfer-learning to a Chronolect](https://md.mova.elamur.ai/free/en/docs/papers/aclbulk-2021-rubinstein-nlp-dh-pipeline-transfer-learning/) *— our card · 2021* 14. [Neural Modeling for Named Entities and Morphology (NEMO2)](https://md.mova.elamur.ai/free/en/docs/papers/tacl-2021-bareket-neural-modeling-named-entities-morphology/) *— our card · 2021 · Transactions of the Association for Computational Linguistics* 15. [A Novel Challenge Set for Hebrew Morphological Disambiguation and Diacritics Restoration](https://md.mova.elamur.ai/free/en/docs/papers/findings-2020-shmidman-novel-challenge-set-hebrew-morphological/) *— our card · 2020 · Findings of the Association for Computational Linguistics: EMNLP 2020* 16. [From SPMRL to NMRL: What Did We Learn (and Unlearn) in a Decade of Parsing Morphologically-Rich Languages (MRLs)?](https://aclanthology.org/2020.acl-main.660/) *— 2020 · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics* 17. cohen-2026-degree-language-diacriticity-its-effect 18. gershov-2021-automatic-speech-based-checklist-medical 19. mondshine-2025-beyond-n-grams-rethinking-evaluation 20. prabhakaran-2023-distinguishing-address-vs-reference-mentions - [← previous Who cites «Constrained Sequence-to-sequence Semitic Root Extraction for Enriching Word Embeddings»](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/aclbulk-2019-kishky-constrained-sequence-sequence-semitic-root/) - [next → Who cites «On the Importance of Tokenization in Arabic Embedding Models»](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/aclbulk-2020-alkaoud-importance-tokenization-arabic-embedding-models/) - [↑ back to papers/cited-by/](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/)