---
title: "Who cites Less, but Better: Efficient — 12 citing papers"
description: "12 papers of the Elamur Research library cite «Less, but Better: Efficient Multilingual Expansion for LLMs via Layer-wise Mixture-of-Experts»…"
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---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/zhang-2025-less-but-better-efficient-multilingual/cited-by/)

[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Less, but Better: Efficient Multilingual…](https://md.research.elamur.ai/free/en/papers/zhang-2025-less-but-better-efficient-multilingual/) / cited by

# Who cites «Less, but Better: Efficient Multilingual Expansion for LLMs via Layer-wise Mixture-of-Experts»

12 papers of our library cite it (of the 149,439 whose bibliographies we read) · 3 with a page here, the most cited first · [← back to «Less, but Better: Efficient Multilingual Expansion for LLMs via Layer-wise Mixture-of-Experts»](https://md.research.elamur.ai/free/en/papers/zhang-2025-less-but-better-efficient-multilingual/)

1. **[Think Natively: Unlocking Multilingual Reasoning with Consistency-Enhanced Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/zhang-2026-think-natively-unlocking-multilingual-reasoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xue Zhang, Yunlong Liang, Fandong Meng, et al.*2026 · 11 citations*
2. **[Language-Coupled Reinforcement Learning for Multilingual Retrieval-Augmented Generation](https://md.research.elamur.ai/free/en/papers/qi-2026-language-coupled-reinforcement-learning-multilingual/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Rui Qi, Fengran Mo, Yufeng Chen, et al.*2026 · 5 citations*
3. **[A Data-Efficient Path to Multilingual LLMs: Language Expansion via Post-training PARAMΔ Integration into Upcycled MoE](https://md.research.elamur.ai/free/en/papers/zhou-2026-data-efficient-path-multilingual-llms/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hao Zhou, Tianhao Li, Zhijun Wang, et al.*2026*

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

- [← back to](https://md.research.elamur.ai/free/en/papers/zhang-2025-less-but-better-efficient-multilingual/) — Less, but Better: Efficient Multilingual Expansion for LLMs via Layer-wise Mixture-of-Experts