--- title: "Who cites Large Pre-Trained Models with Extra-Large…" description: "23 papers of the Elamur Research library cite «Large Pre-Trained Models with Extra-Large Vocabularies: A Contrastive Analysis of Hebrew BERT Models and a…" canonical: "https://research.elamur.ai/free/en/papers/gueta-2022-large-pre-trained-models-extra/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/gueta-2022-large-pre-trained-models-extra/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Large Pre-Trained Models with Extra-Large…](https://md.research.elamur.ai/free/en/papers/gueta-2022-large-pre-trained-models-extra/) / cited by # Who cites «Large Pre-Trained Models with Extra-Large Vocabularies: A Contrastive Analysis of Hebrew BERT Models and a New One to Outperform Them All» 23 papers of our library cite it (of the 140,884 whose bibliographies we read) · 19 with a page here, the most cited first · [← the paper](https://md.research.elamur.ai/free/en/papers/gueta-2022-large-pre-trained-models-extra/) 1. [**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/) 2. [**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/) 3. [**HeQ: a Large and Diverse Hebrew Reading Comprehension Benchmark**Amir DN Cohen, Hilla Merhav, Yoav Goldberg, et al.*2023 · 13 citations*](https://md.research.elamur.ai/free/en/papers/cohen-2023-heq-large-diverse-hebrew-reading/) 4. [**Multilingual Sequence-to-Sequence Models for Hebrew NLP**Matan Eyal, Hila Noga, Roee Aharoni, et al.*2023 · 9 citations*](https://md.research.elamur.ai/free/en/papers/eyal-2023-multilingual-sequence-sequence-models-hebrew/) 5. [**Explicit Morphological Knowledge Improves Pre-training of Language Models for Hebrew**Eylon Gueta, Omer Goldman, Reut Tsarfaty*2023 · 7 citations*](https://md.research.elamur.ai/free/en/papers/gueta-2023-explicit-morphological-knowledge-improves-pre/) 6. [**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/) 7. [**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/) 8. [**TafBERTa: Learning Grammatical Rules from Small-Scale Language Acquisition Data in Hebrew**Anita Gelboim, Elior Sulem*2025 · 3 citations*](https://md.research.elamur.ai/free/en/papers/gelboim-2025-tafberta-learning-grammatical-rules-small/) 9. [**Embible: Reconstruction of Ancient Hebrew and Aramaic Texts Using Transformers**Niv Fono, Harel Moshayof, Eldar Karol, et al.*2024 · 3 citations*](https://md.research.elamur.ai/free/en/papers/fono-2024-embible-reconstruction-ancient-hebrew-aramaic/) 10. [**Temporal Relation Classification in Hebrew**Guy Yanko, Shahaf Pariente, Kfir Bar*2023 · 2 citations*](https://md.research.elamur.ai/free/en/papers/yanko-2023-temporal-relation-classification-hebrew/) 11. [**Hebrew Diacritics Restoration using Visual Representation**Yair Elboher, Yuval Pinter*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/elboher-2026-hebrew-diacritics-restoration-visual-representation/) 12. [**A Classifier of Word-Level Variants in Witnesses of Biblical Hebrew Manuscripts**Iglika Nikolova-Stoupak, Maxime Amblard, Sophie Robert-Hayek, et al.*2025 · 1 citation*](https://md.research.elamur.ai/free/en/papers/stoupak-2025-classifier-word-level-variants-witnesses/) 13. [**LCHAIM - Investigating Long Context Reasoning in Hebrew**Ehud Malul, Oriel Perets, Ziv Mor, et al.*2025 · 1 citation*](https://md.research.elamur.ai/free/en/papers/malul-2025-lchaim-investigating-long-context-reasoning/) 14. [**Restoring Missing Spaces in Scraped Hebrew Social Media**Avi Shmidman, Shaltiel Shmidman*2025 · 1 citation*](https://md.research.elamur.ai/free/en/papers/shmidman-2025-restoring-missing-spaces-scraped-hebrew/) 15. [**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/) 16. [**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/) 17. [**NeoDictaBERT: Pushing the Frontier of BERT models for Hebrew**Shaltiel Shmidman, Avi Shmidman, Moshe Koppel*2025*](https://md.research.elamur.ai/free/en/papers/shmidman-2025-neodictabert-pushing-frontier-bert-models/) 18. [**Systematic Textual Availability of Manuscripts**Hadar Miller, Samuel Londner, Tsvi Kuflik, et al.*2025*](https://md.research.elamur.ai/free/en/papers/miller-2025-systematic-textual-availability-manuscripts/) 19. [**OtoBERT: Identifying Suffixed Verbal Forms in Modern Hebrew Literature**Avi Shmidman, Shaltiel Shmidman*2024*](https://md.research.elamur.ai/free/en/papers/shmidman-2024-otobert-identifying-suffixed-verbal-forms/) 4 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/gueta-2022-large-pre-trained-models-extra/) — Large Pre-Trained Models with Extra-Large Vocabularies: A Contrastive Analysis of Hebrew BERT Models and a New One to Outperform Them All