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Who cites «LLM Pruning and Distillation in Practice: The Minitron Approach»

41 papers of our library cite it (of the 149,439 whose bibliographies we read) · 13 with a page here, the most cited first · ← back to «LLM Pruning and Distillation in Practice: The Minitron Approach»

  1. Magpie: Alignment Data Synthesis from Scratch by Prompting Aligned LLMs with NothingarXiv:2406.08464Zhangchen Xu, Fengqing Jiang, Luyao Niu, et al.2024 · 148 citations
  2. NVIDIA Nemotron Nano 2: An Accurate and Efficient Hybrid Mamba-Transformer Reasoning ModelarXiv:2508.14444NVIDIA: Aarti Basant, Abhijit Khairnar, Abhijit Paithankar, et al.2025 · 39 citations
  3. Nemotron-H: A Family of Accurate and Efficient Hybrid Mamba-Transformer ModelsarXiv:2504.03624NVIDIA: Aaron Blakeman, Aarti Basant, Abhinav Khattar, et al.2025 · 38 citations
  4. A Survey of Small Language ModelsarXiv:2410.20011Chien Van Nguyen, Xuan Shen, Ryan Aponte, et al.2024 · 31 citations
  5. Distillation Scaling LawsarXiv:2502.08606Dan Busbridge, Amitis Shidani, Floris Weers, et al.2025 · 26 citations
  6. Towards Reasoning Ability of Small Language ModelsarXiv:2502.11569Gaurav Srivastava, Shuxiang Cao, Xuan Wang2025 · 16 citations
  7. Pangu Embedded: An Efficient Dual-system LLM Reasoner with MetacognitionarXiv:2505.22375Hanting Chen, Yasheng Wang, Kai Han, et al.2025 · 13 citations

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

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