---
title: "Who cites Chinese Tiny LLM: Pretraining a — 18 citing papers"
description: "18 papers of the Elamur Research library cite «Chinese Tiny LLM: Pretraining a Chinese-Centric Large Language Model», found in their…"
canonical: "https://research.elamur.ai/free/en/papers/du-2024-chinese-tiny-llm-pretraining/cited-by/"
---
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[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Chinese Tiny LLM: Pretraining a Chinese-Centric…](https://md.research.elamur.ai/free/en/papers/du-2024-chinese-tiny-llm-pretraining/) / cited by

# Who cites «Chinese Tiny LLM: Pretraining a Chinese-Centric Large Language Model»

18 papers of our library cite it (of the 149,439 whose bibliographies we read) · 7 with a page here, the most cited first · [← back to «Chinese Tiny LLM: Pretraining a Chinese-Centric Large Language Model»](https://md.research.elamur.ai/free/en/papers/du-2024-chinese-tiny-llm-pretraining/)

1. **[A Comprehensive Survey of Small Language Models in the Era of Large Language Models: Techniques, Enhancements, Applications, Collaboration with LLMs, and Trustworthiness](https://md.research.elamur.ai/free/en/papers/wang-2024-comprehensive-survey-small-language-models/) [ACM Transactions on Intelligent Systems and Technology](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-intelligent-systems-and-technology/)**Fali Wang, Zhiwei Zhang, Xianren Zhang, et al.*2024 · 159 citations*
2. **[Survey of Cultural Awareness in Language Models: Text and Beyond](https://md.research.elamur.ai/free/en/papers/pawar-2025-survey-cultural-awareness-language-models/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Siddhesh Pawar, Junyeong Park, Jiho Jin, et al.*2025 · 106 citations*
3. [**FineWeb2: One Pipeline to Scale Them All — Adapting Pre-Training Data Processing to Every Language arXiv:2506.20920**Guilherme Penedo, Hynek Kydliček, Vinko Sabolčec, et al.*2025 · 99 citations*](https://md.research.elamur.ai/free/en/papers/penedo-2025-fineweb2-one-pipeline-scale-them/)
4. **[DDK: Distilling Domain Knowledge for Efficient Large Language Models](https://md.research.elamur.ai/free/en/papers/liu-2024-ddk-distilling-domain-knowledge-efficient/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Jiaheng Liu, Chenchen Zhang, Jinyang Guo, et al.*2024 · 23 citations*
5. [**Scaling Latent Reasoning via Looped Language Models arXiv:2510.25741**Rui-Jie Zhu, Zixuan Wang, Kai Hua, et al.*2025 · 22 citations*](https://md.research.elamur.ai/free/en/papers/zhu-2025-scaling-latent-reasoning-looped-language/)
6. **[Alignment at Pre-training! Towards Native Alignment for Arabic LLMs](https://md.research.elamur.ai/free/en/papers/liang-2024-alignment-pre-training-towards-native/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Juhao Liang, Zhenyang Cai, Jianqing Zhu, et al.*2024 · 14 citations*
7. **[MERLIN: Multi-Stage Curriculum Alignment for Multilingual Encoder-LLM Integration in Cross-Lingual Reasoning](https://md.research.elamur.ai/free/en/papers/uemura-2026-merlin-multi-stage-curriculum-alignment/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Kosei Uemura, David Guzmán, Quang Phuoc Nguyen, et al.*2026 · 1 citation*

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

- [← back to](https://md.research.elamur.ai/free/en/papers/du-2024-chinese-tiny-llm-pretraining/) — Chinese Tiny LLM: Pretraining a Chinese-Centric Large Language Model