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# Who cites «Joint Transition-Based Models for Morpho-Syntactic Parsing: Parsing Strategies for MRLs and a Case Study from Modern Hebrew»

23 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/tacl-2019-more-joint-transition-based-models-morpho/)

1. [Arabic Morphosyntactic Tagging and Dependency Parsing with Large Language Models](https://md.mova.elamur.ai/free/en/docs/papers/langstream-2026-adel-arabic-morphosyntactic-tagging-dependency-parsing/) *— our card · 2026 · arXiv:2603.16718*
2. [TafBERTa: Learning Grammatical Rules from Small-Scale Language Acquisition Data in Hebrew](https://md.mova.elamur.ai/free/en/docs/papers/babylm-2025-gelboim-tafberta-learning-grammatical-rules-small/) *— our card · 2025 · Proceedings of the First BabyLM Workshop*
3. [A Truly Joint Neural Architecture for Segmentation and Parsing](https://md.mova.elamur.ai/free/en/docs/papers/eacl-2024-levi-truly-joint-neural-architecture-segmentation/) *— our card · 2024 · Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers)*
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. [CamelParser2.0: A State-of-the-Art Dependency Parser for Arabic](https://md.mova.elamur.ai/free/en/docs/papers/ud-2023-elshabrawy-camelparser2-0-state-art-dependency/) *— our card · 2023 · Proceedings of ArabicNLP 2023*
6. [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*
7. [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*
8. [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*
9. [Systematic Investigation of Strategies Tailored for Low-Resource Settings for Low-Resource Dependency Parsing](https://aclanthology.org/2023.eacl-main.158/) *— 2023 · Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics*
10. [AlephBERT: Language Model Pre-training and Evaluation from Sub-Word to Sentence Level](https://md.mova.elamur.ai/free/en/docs/papers/acl-2022-seker-alephbert-language-model-pre-training/) *— our card · 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
11. [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*
12. [HeBERT & HebEMO: a Hebrew BERT Model and a Tool for Polarity Analysis and Emotion Recognition](https://md.mova.elamur.ai/free/en/docs/papers/langstream-2021-chriqui-hebert-hebemo-hebrew-bert-model/) *— our card · 2021 · arXiv:2102.01909*
13. [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*
14. [A Graph-Based Framework for Structured Prediction Tasks in Sanskrit](https://aclanthology.org/2020.cl-4.4/) *— 2020 · Computational Linguistics*
15. [A Pointer Network Architecture for Joint Morphological Segmentation and Tagging](https://md.mova.elamur.ai/free/en/docs/papers/ud-2020-seker-pointer-network-architecture-joint-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. [Getting the \#\#life out of living: How Adequate Are Word-Pieces for Modelling Complex Morphology?](https://aclanthology.org/2020.sigmorphon-1.24/) *— 2020 · Proceedings of the 17th SIGMORPHON Workshop on Computational Research in Phonetics, Phonology, and Morphology*
18. [Keep it Surprisingly Simple: A Simple First Order Graph Based Parsing Model for Joint Morphosyntactic Parsing in Sanskrit](https://aclanthology.org/2020.emnlp-main.388/) *— 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)*
19. [SHR++: An Interface for Morpho-syntactic Annotation of Sanskrit Corpora](https://aclanthology.org/2020.lrec-1.874/) *— 2020 · Proceedings of the Twelfth Language Resources and Evaluation Conference*
20. [What's Wrong with Hebrew NLP? And How to Make it Right](https://md.mova.elamur.ai/free/en/docs/papers/aclbulk-2019-tsarfaty-what-s-wrong-hebrew-nlp/) *— our card · 2019 · Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP): System Demonstrations*
21. gershov-2021-automatic-speech-based-checklist-medical
22. [hagag-2023-truth-whole-truth-nothing-but](https://md.mova.elamur.ai/free/en/docs/papers/findings-2023-hagag-truth-whole-truth-nothing-but/) *— our card*
23. [miller-2025-systematic-textual-availability-manuscripts](https://md.mova.elamur.ai/free/en/docs/papers/aclbulk-2025-miller-systematic-textual-availability-manuscripts/) *— our card*
- [← previous Who cites «A Graph-based Lattice Dependency Parser for Joint Morphological Segmentation and Syntactic Analysis»](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/tacl-2015-seeker-graph-based-lattice-dependency-parser/)
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