---
title: "Who cites HeRo: RoBERTa and Longformer Hebrew Language…"
description: "14 papers of the Elamur Research library cite «HeRo: RoBERTa and Longformer Hebrew Language Models», found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/papers/shalumov-2023-hero-roberta-longformer-hebrew-language/cited-by/"
---
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[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [HeRo: RoBERTa and Longformer Hebrew Language…](https://md.research.elamur.ai/free/en/papers/shalumov-2023-hero-roberta-longformer-hebrew-language/) / cited by

# Who cites «HeRo: RoBERTa and Longformer Hebrew Language Models»

14 papers of our library cite it (of the 140,884 whose bibliographies we read) · 10 with a page here, the most cited first · [← the paper](https://md.research.elamur.ai/free/en/papers/shalumov-2023-hero-roberta-longformer-hebrew-language/)

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. [**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/)
3. [**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/)
4. [**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/)
5. [**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/)
6. [**Introducing DictaLM — A Large Generative Language Model for Modern Hebrew**Shaltiel Shmidman, Avi Shmidman, Amir David Nissan Cohen, et al.*2023 · 1 citation*](https://md.research.elamur.ai/free/en/papers/shmidman-2023-introducing-dictalm-large-generative-language/)
7. [**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/)
8. [**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/)
9. [**Hierarchical Section Matching Prediction (HSMP) BERT for Fine-Grained Extraction of Structured Data from Hebrew Free-Text Radiology Reports in Crohn's Disease**Zvi Badash; Hadas Ben-Atya; Naama Gavrielov; Liam Hazan; Gili Focht; Ruth Cytter-Kuint; Talar Hagopian; Dan Turner;, Moti Freiman*2025*](https://md.research.elamur.ai/free/en/papers/badash-2025-hierarchical-section-matching-prediction-hsmp/)
10. [**Mevaker: Conclusion Extraction and Allocation Resources for the Hebrew Language**Vitaly Shalumov, Harel Haskey, Yuval Solaz*2024*](https://md.research.elamur.ai/free/en/papers/shalumov-2024-mevaker-conclusion-extraction-allocation-resources/)

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

- [← back to](https://md.research.elamur.ai/free/en/papers/shalumov-2023-hero-roberta-longformer-hebrew-language/) — HeRo: RoBERTa and Longformer Hebrew Language Models