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Who cites «Microscaling Data Formats for Deep Learning»

70 papers of our library cite it (of the 149,439 whose bibliographies we read) · 10 with a page here, the most cited first · ← back to «Microscaling Data Formats for Deep Learning»

  1. Atom: Low-bit Quantization for Efficient and Accurate LLM ServingMLSys 2024Yilong Zhao, Chien-Yu Lin, Kan Zhu, et al.2023 · 156 citations
  2. DeepSeek-V4: Towards Highly Efficient Million-Token Context IntelligencearXiv:2606.19348DeepSeek-AI, Anyi Xu, Bangcai Lin, et al.2026 · 122 citations
  3. QServe: W4A8KV4 Quantization and System Co-design for Efficient LLM ServingMLSys 2025Yujun Lin, Haotian Tang, Shang Yang, et al.2024 · 120 citations
  4. Kimi K3: Open Frontier IntelligencearXiv:2607.24653Kimi Team, Tongtong Bai, Yifan Bai, et al.2026 · 40 citations
  5. DeepSeek-V4.1-Flash: Pushing the Limits of KV Cache CompressionarXiv:2609.19969DeepSeek-AI, Anyi Xu, B. Li, et al.2026 · 3 citations

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

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