---
title: "Who cites AlephBERT: A Hebrew Large Pre-Trained Language…"
description: "34 papers of the Elamur Research library cite «AlephBERT: A Hebrew Large Pre-Trained Language Model to Start-off your Hebrew NLP Application With», found…"
canonical: "https://research.elamur.ai/free/en/papers/seker-2021-alephbert-hebrew-large-pre-trained/cited-by/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/seker-2021-alephbert-hebrew-large-pre-trained/cited-by/)

[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [AlephBERT: A Hebrew Large Pre-Trained Language…](https://md.research.elamur.ai/free/en/papers/seker-2021-alephbert-hebrew-large-pre-trained/) / cited by

# Who cites «AlephBERT: A Hebrew Large Pre-Trained Language Model to Start-off your Hebrew NLP Application With»

34 papers of our library cite it (of the 140,884 whose bibliographies we read) · 25 with a page here, the most cited first · [← the paper](https://md.research.elamur.ai/free/en/papers/seker-2021-alephbert-hebrew-large-pre-trained/)

1. [**Recent Advances in Natural Language Processing via Large Pre-Trained Language Models: A Survey**Bonan Min, Hayley Ross, Elior Sulem, et al.*2021 · 1,548 citations*](https://md.research.elamur.ai/free/en/papers/min-2021-recent-advances-natural-language-processing/)
2. [**Quality at a Glance: An Audit of Web-Crawled Multilingual Datasets**Julia Kreutzer, Isaac Caswell, Lisa Wang, et al.*2021 · 447 citations*](https://md.research.elamur.ai/free/en/papers/kreutzer-2021-quality-glance-audit-web-crawled/)
3. [**Large Pre-Trained Models with Extra-Large Vocabularies: A Contrastive Analysis of Hebrew BERT Models and a New One to Outperform Them All**Eylon Gueta, Avi Shmidman, Shaltiel Shmidman, et al.*2022 · 28 citations*](https://md.research.elamur.ai/free/en/papers/gueta-2022-large-pre-trained-models-extra/)
4. [**DictaBERT: A State-of-the-Art BERT Suite for Modern Hebrew**Shaltiel Shmidman, Avi Shmidman, Moshe Koppel*2023 · 22 citations*](https://md.research.elamur.ai/free/en/papers/shmidman-2023-dictabert-state-art-bert-suite/)
5. [**HeRo: RoBERTa and Longformer Hebrew Language Models**Vitaly Shalumov, Harel Haskey*2023 · 15 citations*](https://md.research.elamur.ai/free/en/papers/shalumov-2023-hero-roberta-longformer-hebrew-language/)
6. [**Introducing BEREL: BERT Embeddings for Rabbinic-Encoded Language**Avi Shmidman, Joshua Guedalia, Shaltiel Shmidman, et al.*2022 · 13 citations*](https://md.research.elamur.ai/free/en/papers/shmidman-2022-introducing-berel-bert-embeddings-rabbinic/)
7. [**ParaShoot: A Hebrew Question Answering Dataset**Omri Keren, Omer Levy*2021 · 12 citations*](https://md.research.elamur.ai/free/en/papers/keren-2021-parashoot-hebrew-question-answering-dataset/)
8. [**Offensive Hebrew Corpus and Detection using BERT**Nagham Hamad, Mustafa Jarrar, Mohammad Khalilia, et al.*2023 · 11 citations*](https://md.research.elamur.ai/free/en/papers/hamad-2023-offensive-hebrew-corpus-detection-using/)
9. [**MRL Parsing Without Tears: The Case of Hebrew**Shaltiel Shmidman, Avi Shmidman, Moshe Koppel, et al.*2024 · 8 citations*](https://md.research.elamur.ai/free/en/papers/shmidman-2024-mrl-parsing-without-tears-case/)
10. [**A Truly Joint Neural Architecture for Segmentation and Parsing**Danit Yshaayahu Levi, Reut Tsarfaty*2024 · 7 citations*](https://md.research.elamur.ai/free/en/papers/levi-2024-truly-joint-neural-architecture-segmentation/)
11. [**ivrit.ai: A Comprehensive Dataset of Hebrew Speech for AI Research and Development**Yanir Marmor, Kinneret Misgav, Yair Lifshitz*2023 · 6 citations*](https://md.research.elamur.ai/free/en/papers/marmor-2023-ivrit-ai-comprehensive-dataset-hebrew/)
12. [**A Transformer-based parser for Syriac morphology**Martijn Naaijer, Constantijn Sikkel, Mathias Coeckelbergs, et al.*2023 · 5 citations*](https://md.research.elamur.ai/free/en/papers/naaijer-2023-transformer-based-parser-syriac-morphology/)
13. [**Do Pretrained Contextual Language Models Distinguish between Hebrew Homograph Analyses?**Avi Shmidman, Cheyn Shmuel Shmidman, Dan Bareket, et al.*2023 · 5 citations*](https://md.research.elamur.ai/free/en/papers/shmidman-2023-do-pretrained-contextual-language-models/)
14. [**MsBERT: A New Model for the Reconstruction of Lacunae in Hebrew Manuscripts**Avi Shmidman, Ometz Shmidman, Hillel Gershuni, et al.*2024 · 4 citations*](https://md.research.elamur.ai/free/en/papers/shmidman-2024-msbert-new-model-reconstruction-lacunae/)
15. [**A Dataset for Metaphor Detection in Early Medieval Hebrew Poetry**Michael Toker, Oren Mishali, Ophir Münz-Manor, et al.*2024 · 3 citations*](https://md.research.elamur.ai/free/en/papers/toker-2024-dataset-metaphor-detection-early-medieval/)
16. [**A Language Modeling Approach to Diacritic-Free Hebrew TTS**Amit Roth, Arnon Turetzky, Yossi Adi*2024 · 3 citations*](https://md.research.elamur.ai/free/en/papers/roth-2024-language-modeling-approach-diacritic-free/)
17. [**From Linguistics to Practice: a Case Study of Offensive Language Taxonomy in Hebrew**Chaya Liebeskind, Marina Litvak, Natalia Vanetik*2024 · 2 citations*](https://md.research.elamur.ai/free/en/papers/liebeskind-2024-linguistics-practice-case-study-offensive/)
18. [**Intertextual Parallel Detection in Biblical Hebrew: A Transformer-Based Benchmark**David M. Smiley*2025 · 1 citation*](https://md.research.elamur.ai/free/en/papers/smiley-2025-intertextual-parallel-detection-biblical-hebrew/)
19. [**Enhancing TTS Stability in Hebrew using Discrete Semantic Units**Ella Zeldes, Or Tal, Yossi Adi*2024 · 1 citation*](https://md.research.elamur.ai/free/en/papers/zeldes-2024-enhancing-tts-stability-hebrew-using/)
20. [**Detection of Negative Campaign in Israeli Municipal Elections**Marina Litvak, Natalia Vanetik, Sagiv Talker, et al.*2022 · 1 citation*](https://md.research.elamur.ai/free/en/papers/litvak-2022-detection-negative-campaign-israeli-municipal/)
21. [**Word-Embeddings Distinguish Denominal and Root-Derived Verbs in Semitic**Ido Benbaji, Omri Doron, Adele Henot-Mortier*2022 · 1 citation*](https://md.research.elamur.ai/free/en/papers/benbaji-2022-word-embeddings-distinguish-denominal-root/)
22. [**Annotation Matters: Resolving Cross-Corpus Performance Drops in Hebrew Offensive Language Detection**Gili Berger Hefetz, Yossef Haim Shrem, Natalia Vanetik, et al.*2026*](https://md.research.elamur.ai/free/en/papers/hefetz-2026-annotation-matters-resolving-cross-corpus/)
23. [**HalleluBERT: Let Every Token That Has Meaning Bear Its Weight**Raphael Schmitt*2026*](https://md.research.elamur.ai/free/en/papers/schmitt-2026-hallelubert-let-every-token-that/)
24. [**MiqraBERT: Regression-Based Sentence-BERT Finetuning for Biblical Hebrew Parallel Detection**David M. Smiley*2026*](https://md.research.elamur.ai/free/en/papers/smiley-2026-miqrabert-regression-based-sentence-bert/)
25. [**The Truth, The Whole Truth, and Nothing but the Truth: A New Benchmark Dataset for Hebrew Text Credibility Assessment**Ben Hagag, Reut Tsarfaty*2023*](https://md.research.elamur.ai/free/en/papers/hagag-2023-truth-whole-truth-nothing-but/)

9 more papers of our library cite it; they have no page here yet.

- [← back to](https://md.research.elamur.ai/free/en/papers/seker-2021-alephbert-hebrew-large-pre-trained/) — AlephBERT: A Hebrew Large Pre-Trained Language Model to Start-off your Hebrew NLP Application With