---
title: "Who cites A Pointer Network Architecture for Joint…"
description: "The papers of the Elamur Research library that cite «A Pointer Network Architecture for Joint Morphological Segmentation and Tagging», found in their…"
canonical: "https://research.elamur.ai/free/en/papers/ud-2020-seker-pointer-network-architecture-joint-morphological/cited-by/"
---
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# Who cites «A Pointer Network Architecture for Joint Morphological Segmentation and Tagging»

12 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/ud-2020-seker-pointer-network-architecture-joint-morphological/)

1. [Neural Morphological Tagging for Nguni Languages](https://aclanthology.org/2025.africanlp-1.31/) *— 2025 · Proceedings of the Sixth Workshop on African Natural Language Processing (AfricaNLP 2025)*
2. [A Truly Joint Neural Architecture for Segmentation and Parsing](https://md.research.elamur.ai/free/en/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)*
3. [MRL Parsing Without Tears: The Case of Hebrew](https://md.research.elamur.ai/free/en/papers/findings-2024-shmidman-mrl-parsing-without-tears-case/) *— our card · 2024 · Findings of the Association for Computational Linguistics: ACL 2024*
4. [MenakBERT -- Hebrew Diacriticizer](https://md.research.elamur.ai/free/en/papers/hbo-2024-cohen-menakbert-hebrew-diacriticizer/) *— our card · 2024 · arXiv:2410.02417*
5. [Joint Learning Model for Low-Resource Agglutinative Language Morphological Tagging](https://aclanthology.org/2023.sigmorphon-1.4/) *— 2023 · Proceedings of the 20th SIGMORPHON workshop on Computational Research in Phonetics, Phonology, and Morphology*
6. [Text Rendering Strategies for Pixel Language Models](https://aclanthology.org/2023.emnlp-main.628/) *— 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing*
7. [AlephBERT: Language Model Pre-training and Evaluation from Sub-Word to Sentence Level](https://md.research.elamur.ai/free/en/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)*
8. [An Embarrassingly Simple Method to Mitigate Undesirable Properties of Pretrained Language Model Tokenizers](https://aclanthology.org/2022.acl-short.43/) *— 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)*
9. [Morphological Processing of Low-Resource Languages: Where We Are and What”s Next](https://aclanthology.org/2022.findings-acl.80/) *— 2022 · Findings of ACL 2022 (Dublin)*
10. [AlephBERT:A Hebrew Large Pre-Trained Language Model to Start-off your Hebrew NLP Application With](https://md.research.elamur.ai/free/en/papers/langstream-2021-seker-alephbert-hebrew-large-pre-trained/) *— our card · 2021 · arXiv:2104.04052*
11. [Neural Modeling for Named Entities and Morphology (NEMO2)](https://md.research.elamur.ai/free/en/papers/tacl-2021-bareket-neural-modeling-named-entities-morphology/) *— our card · 2021 · Transactions of the Association for Computational Linguistics*
12. [You should evaluate your language model on marginal likelihood over tokenisations](https://aclanthology.org/2021.emnlp-main.161/) *— 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing*