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Who cites «PaD: Program-aided Distillation Can Teach Small Models Reasoning Better than Chain-of-thought Fine-tuning»

28 papers of our library cite it (of the 149,439 whose bibliographies we read) · 11 with a page here, the most cited first · ← back to «PaD: Program-aided Distillation Can Teach Small Models Reasoning Better than Chain-of-thought Fine-tuning»

  1. Navigate through Enigmatic Labyrinth A Survey of Chain of Thought Reasoning: Advances, Frontiers and FuturearXiv:2309.15402Zheng Chu, Jingchang Chen, Qianglong Chen, et al.2023 · 125 citations
  2. A Survey on Efficient Inference for Large Language ModelsarXiv:2404.14294Zixuan Zhou, Xuefei Ning, Ke Hong, et al.2024 · 113 citations
  3. A Survey of Resource-efficient LLM and Multimodal Foundation ModelsarXiv:2401.08092Mengwei Xu, Wangsong Yin, Dongqi Cai, et al.2024 · 54 citations
  4. Large Language Models are Zero Shot Hypothesis ProposersarXiv:2311.05965Biqing Qi, Kaiyan Zhang, Haoxiang Li, et al.2023 · 45 citations
  5. Large Language Models as Biomedical Hypothesis Generators: A Comprehensive EvaluationarXiv:2407.08940Biqing Qi, Kaiyan Zhang, Kai Tian, et al.2024 · 19 citations
  6. Distilling LLM Agent into Small Models with Retrieval and Code ToolsarXiv:2505.17612Minki Kang, Jongwon Jeong, Seanie Lee, et al.2025 · 11 citations
  7. Mixed Distillation Helps Smaller Language Model Better ReasoningarXiv:2312.10730Chenglin Li, Qianglong Chen, Liangyue Li, et al.2023 · 11 citations

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

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