🔗 Who cites «Data Mixing Laws: Optimizing Data Mixtures by Predicting Language Modeling Performance»

50 papers of our library cite it (of the 149,439 whose bibliographies we read) · 15 with a page here, the most cited first · ← back to «Data Mixing Laws: Optimizing Data Mixtures by Predicting Language Modeling Performance»

1. MiniCPM: Unveiling the Potential of Small Language Models with Scalable Training StrategiesarXiv:2404.06395Shengding Hu, Yuge Tu, Xu Han, et al.2024 · 269 citations
2. Olmo 3arXiv:2512.13961Team Olmo: Allyson Ettinger, Amanda Bertsch, Bailey Kuehl, et al.2025 · 130 citations
3. A Survey on Data Selection for Language ModelsarXiv:2402.16827Alon Albalak, Yanai Elazar, Sang Michael Xie, et al.2024 · 95 citations
4. RegMix: Data Mixture as Regression for Language Model Pre-trainingarXiv:2407.01492Qian Liu, Xiaosen Zheng, Niklas Muennighoff, et al.2024 · 57 citations
5. DDK: Distilling Domain Knowledge for Efficient Large Language ModelsConference on Neural Information Processing Systems (NeurIPS)Jiaheng Liu, Chenchen Zhang, Jinyang Guo, et al.2024 · 23 citations
6. Surveying the Effects of Quality, Diversity, and Complexity in Synthetic Data From Large Language ModelsarXiv:2412.02980Alex Havrilla, Andrew Dai, Laura O'Mahony, et al.2024 · 17 citations
7. MiniPLM: Knowledge Distillation for Pre-Training Language ModelsarXiv:2410.17215Yuxian Gu, Hao Zhou, Fandong Meng, et al.2024 · 12 citations
8. Data Mixing Agent: Learning to Re-weight Domains for Continual Pre-trainingAnnual Meeting of the Association for Computational Linguistics (ACL)Kailai Yang, Xiao Liu, Lei Ji, et al.2026 · 1 citation
9. DaMo: Data Mixing Optimizer in Fine-tuning Multimodal LLMs for Mobile Phone AgentsFindings of the Association for Computational LinguisticsKai Shi, Jun Yang, Ni Yang, et al.2026
10. Data Foundations of Long-Context Language Models: A SurveyTransactions of the Association for Computational Linguistics (TACL)Zechen Sun, Yuyang Sun, Zhaochen Su, et al.2026
11. Rethinking Data Mixing from the Perspective of Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Yuanjian Xu, Tianze Sun, Changwei Xu, et al.2026
12. Rethinking Data Mixture for Large Language Models: A Comprehensive Survey and New PerspectivesFindings of the Association for Computational LinguisticsYajiao Liu, Congliang Chen, Junchi Yang, et al.2026
13. TiKMiX: Efficient Semi-Dynamic Data Mixture via Data Influence for LLM Pre-trainingAnnual Meeting of the Association for Computational Linguistics (ACL)Yifan Wang, Binbinliu, Fengze Liu, et al.2026
14. TReX: Tokenizer Regression for Optimal Data MixtureConference of the European Chapter of the Association for Computational Linguistics (EACL)Inho Won, Hangyeol Yoo, Minkyung Cho, et al.2026
15. 360Zhinao Technical ReportarXiv:2405.133862024

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

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