--- title: "Who cites Liqun Ma — 46 papers of our library — Elamur Research" description: "46 papers of the Elamur Research library cite the works of Liqun Ma, found in their bibliographies; the most cited first." canonical: "https://research.elamur.ai/free/en/authors/liqun-ma/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/liqun-ma/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / [Liqun Ma](https://md.research.elamur.ai/free/en/authors/liqun-ma/) / cited by # Who cites Liqun Ma 46 citations of their works from 46 papers of our library (of the 149,439 whose bibliographies we read) · 18 with a page here, the most cited first · [← Liqun Ma](https://md.research.elamur.ai/free/en/authors/liqun-ma/) 1. **[A Survey of Large Language Models](https://md.research.elamur.ai/free/en/papers/zhao-2023-survey-large-language-models/) [Frontiers of Computer Science](https://md.research.elamur.ai/free/en/venues/frontiers-of-computer-science/)**Wayne Xin Zhao, Kun Zhou, Junyi Li, et al.*2023 · 2,875 citations* 2. **[RedPajama: an Open Dataset for Training Large Language Models](https://md.research.elamur.ai/free/en/papers/weber-2024-redpajama-open-dataset-training-large/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Maurice Weber, Daniel Fu, Quentin Anthony, et al.*2024 · 260 citations* 3. [**Fanar: An Arabic-Centric Multimodal Generative AI Platform arXiv:2501.13944**Fanar Team: Ummar Abbas, Mohammad Shahmeer Ahmad, Firoj Alam, et al.*2025 · 127 citations*](https://md.research.elamur.ai/free/en/papers/abbas-2025-fanar-arabic-centric-multimodal-generative/) 4. [**SaulLM-7B: A pioneering Large Language Model for Law arXiv:2403.03883**Pierre Colombo, Telmo Pessoa Pires, Malik Boudiaf, et al.*2024 · 119 citations*](https://md.research.elamur.ai/free/en/papers/colombo-2024-saullm-7b-pioneering-large-language/) 5. [**A Survey on Data Selection for Language Models arXiv:2402.16827**Alon Albalak, Yanai Elazar, Sang Michael Xie, et al.*2024 · 95 citations*](https://md.research.elamur.ai/free/en/papers/albalak-2024-survey-data-selection-language-models/) 6. **[Rephrasing the Web: A Recipe for Compute and Data-Efficient Language Modeling](https://md.research.elamur.ai/free/en/papers/maini-2024-rephrasing-web-recipe-compute-data/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Pratyush Maini, Skyler Seto, Richard Bai, et al.*2024 · 90 citations* 7. [**SuperGPQA: Scaling LLM Evaluation across 285 Graduate Disciplines arXiv:2502.14739**M-A-P Team, Xinrun Du, Yifan Yao, et al.*2025 · 89 citations*](https://md.research.elamur.ai/free/en/papers/team-2025-supergpqa-scaling-llm-evaluation-across/) 8. **[Apertus: Democratizing Open and Compliant LLMs for Global Language Environments](https://md.research.elamur.ai/free/en/papers/cano-2026-apertus-democratizing-open-compliant-llms/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Alejandro Hernández-Cano, Alexander Hägele, Allen Hao Huang, et al.*2026 · 68 citations* 9. [**Maximize Your Data's Potential: Enhancing LLM Accuracy with Two-Phase Pretraining arXiv:2412.15285**Steven Feng, Shrimai Prabhumoye, Kezhi Kong, et al.*2024 · 12 citations*](https://md.research.elamur.ai/free/en/papers/feng-2024-maximize-data-s-potential-enhancing/) 10. [**SIaM: Self-Improving Code-Assisted Mathematical Reasoning of Large Language Models arXiv:2408.15565**Dian Yu, Baolin Peng, Ye Tian, et al.*2024 · 8 citations*](https://md.research.elamur.ai/free/en/papers/yu-2024-siam-self-improving-code-assisted/) 11. **[Language Adaptation of Large Language Models: An Empirical Study on LLaMA2](https://md.research.elamur.ai/free/en/papers/wang-2025-language-adaptation-large-language-models/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Shumin Wang, Yuexiang Xie, Bolin Ding, et al.*2025 · 7 citations* 12. **[Bit-by-Bit: Progressive QAT Strategy with Outlier Channel Splitting for Stable Low-Bit LLMs](https://md.research.elamur.ai/free/en/papers/xu-2026-bit-bit-progressive-qat-strategy/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Binxing Xu, Hao Gu, Lujun Li, et al.*2026 · 3 citations* 13. **[Data Mixing Agent: Learning to Re-weight Domains for Continual Pre-training](https://md.research.elamur.ai/free/en/papers/yang-2026-data-mixing-agent-learning-re/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Kailai Yang, Xiao Liu, Lei Ji, et al.*2026 · 1 citation* 14. **[LBLLM: Lightweight Binarization of Large Language Models via Three-Stage Distillation](https://md.research.elamur.ai/free/en/papers/song-2026-lbllm-lightweight-binarization-large-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Siqing Song, Chuang Wang, Yong Lang, et al.*2026* 15. **[LLMSurgeon: Diagnosing Data Mixture of Large Language Models](https://md.research.elamur.ai/free/en/papers/luo-2026-llmsurgeon-diagnosing-data-mixture-large/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yaxin Luo, Jiacheng Cui, Xiaohan Zhao, et al.*2026* 16. **[pQuant: Towards Effective Low-Bit Language Models via Decoupled Linear Quantization-Aware Training](https://md.research.elamur.ai/free/en/papers/zhang-2026-pquant-effective-low-bit-language/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Wenzheng Zhang, Bingzheng Liu*2026* 17. **[Rethinking Data Mixture for Large Language Models: A Comprehensive Survey and New Perspectives](https://md.research.elamur.ai/free/en/papers/liu-2026-rethinking-data-mixture-large-language/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yajiao Liu, Congliang Chen, Junchi Yang, et al.*2026* 18. [**360Zhinao Technical Report arXiv:2405.13386***2024*](https://md.research.elamur.ai/free/en/papers/360zhinao-team-2024-360zhinao-technical-report/) 28 more citing papers of our library have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/authors/liqun-ma/) — Liqun Ma