---
title: "Who cites Scaling Low-Resource MT via — 11 citing papers"
description: "11 papers of the Elamur Research library cite «Scaling Low-Resource MT via Synthetic Data Generation with LLMs», found in their…"
canonical: "https://research.elamur.ai/free/en/papers/gibert-2025-scaling-low-resource-mt-synthetic/cited-by/"
---
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[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Scaling Low-Resource MT via Synthetic Data…](https://md.research.elamur.ai/free/en/papers/gibert-2025-scaling-low-resource-mt-synthetic/) / cited by

# Who cites «Scaling Low-Resource MT via Synthetic Data Generation with LLMs»

11 papers of our library cite it (of the 149,439 whose bibliographies we read) · 4 with a page here, the most cited first · [← back to «Scaling Low-Resource MT via Synthetic Data Generation with LLMs»](https://md.research.elamur.ai/free/en/papers/gibert-2025-scaling-low-resource-mt-synthetic/)

1. **[HPLT 3.0: Very Large-Scale Multilingual Resources for LLMs and MT. Mono- and Bi-lingual Data, Multilingual Evaluation, and Pre-Trained Models](https://md.research.elamur.ai/free/en/papers/oepen-2026-hplt-3-0-very-large/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Stephan Oepen, Nikolay Arefyev, Mikko Aulamo, et al.*2026 · 1 citation*
2. **[When LLMs Annotate: Reliability Challenges in Low-Resource NLI](https://md.research.elamur.ai/free/en/papers/panahi-2026-when-llms-annotate-reliability-challenges/) [Workshop on Language Models for Low-Resource Languages](https://md.research.elamur.ai/free/en/venues/loreslm/)**Solmaz Panahi, John Kelleher, Vasudevan Nedumpozhimana*2026 · 1 citation*
3. **[Bi-Text Mining across German Dialects: On the Role of Synthetic Training Data for Dialect Adaptation](https://md.research.elamur.ai/free/en/papers/wang-2026-bi-text-mining-across-german/) [Workshop on Building and Using Comparable Corpora (BUCC)](https://md.research.elamur.ai/free/en/venues/bucc/)**Jing Wang, Barbara Plank, Robert Litschko*2026*
4. **[Thesis Proposal: Diagnosing and Mitigating Semantic Interference in Script-Sharing Low-Resource Language Models: A Case Study on Square Bai Script](https://md.research.elamur.ai/free/en/papers/zheng-2026-thesis-proposal-diagnosing-mitigating-semantic/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jingting Zheng, Deyi Xiong*2026*

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

- [← back to](https://md.research.elamur.ai/free/en/papers/gibert-2025-scaling-low-resource-mt-synthetic/) — Scaling Low-Resource MT via Synthetic Data Generation with LLMs