---
title: "Who cites Efficient Methods for Natural — 42 citing papers"
description: "42 papers of the Elamur Research library cite «Efficient Methods for Natural Language Processing: A Survey», found in their bibliographies…"
canonical: "https://research.elamur.ai/free/en/papers/treviso-2023-efficient-methods-natural-language-processing/cited-by/"
---
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[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Efficient Methods for Natural Language…](https://md.research.elamur.ai/free/en/papers/treviso-2023-efficient-methods-natural-language-processing/) / cited by

# Who cites «Efficient Methods for Natural Language Processing: A Survey»

42 papers of our library cite it (of the 141,840 whose bibliographies we read) · 3 with a page here, the most cited first · [← back to «Efficient Methods for Natural Language Processing: A Survey»](https://md.research.elamur.ai/free/en/papers/treviso-2023-efficient-methods-natural-language-processing/)

1. [**Aya Model: An Instruction Finetuned Open-Access Multilingual Language Model**Ahmet Üstün, Viraat Aryabumi, Zheng-Xin Yong, et al.*2024 · 245 citations*](https://md.research.elamur.ai/free/en/papers/ustun-2024-aya-model-instruction-finetuned-open/)
2. [**HatePrototypes: Interpretable and Transferable Representations for Implicit and Explicit Hate Speech Detection**Irina Proskurina, Marc-Antoine Carpentier, Julien Velcin*2026*](https://md.research.elamur.ai/free/en/papers/proskurina-2026-hateprototypes-interpretable-transferable-representations-implicit/)
3. [**Integrating AI into Arabic Linguistics: A Methodological Framework for Reproducible and Interpretable Research**Ismail Akzam, Mohammad Ikhwan Bin Abdullah*2026*](https://md.research.elamur.ai/free/en/papers/akzam-2026-integrating-ai-arabic-linguistics-methodological/)

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

- [← back to](https://md.research.elamur.ai/free/en/papers/treviso-2023-efficient-methods-natural-language-processing/) — Efficient Methods for Natural Language Processing: A Survey
