---
title: "Who cites Neural Modeling for Named Entities and…"
description: "14 papers of the Elamur Research library cite «Neural Modeling for Named Entities and Morphology (NEMO2)», found in their bibliographies; the most cited…"
canonical: "https://research.elamur.ai/free/en/papers/bareket-2021-neural-modeling-named-entities-morphology/cited-by/"
---
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# Who cites «Neural Modeling for Named Entities and Morphology (NEMO2)»

14 papers of our library cite it (of the 140,884 whose bibliographies we read) · 8 with a page here, the most cited first · [← the paper](https://md.research.elamur.ai/free/en/papers/bareket-2021-neural-modeling-named-entities-morphology/)

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. [**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/)
3. [**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/)
4. [**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/)
5. [**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/)
6. [**Beyond Word Boundaries: A Hebrew Coreference Benchmark and an Evaluation Protocol for Morphologically Complex Text**Refael Shaked Greenfeld, Reut Tsarfaty*2026*](https://md.research.elamur.ai/free/en/papers/greenfeld-2026-beyond-word-boundaries-hebrew-coreference/)
7. [**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/)
8. [**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/)

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

- [← back to](https://md.research.elamur.ai/free/en/papers/bareket-2021-neural-modeling-named-entities-morphology/) — Neural Modeling for Named Entities and Morphology (NEMO2)
