---
title: "Who cites MagicPIG: LSH Sampling for Efficient LLM Generation"
description: "64 papers of the Elamur Research library cite «MagicPIG: LSH Sampling for Efficient LLM Generation», found in their bibliographies; the most…"
canonical: "https://research.elamur.ai/free/en/papers/chen-2024-magicpig-lsh-sampling-efficient-llm/cited-by/"
---
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[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [MagicPIG: LSH Sampling for Efficient LLM…](https://md.research.elamur.ai/free/en/papers/chen-2024-magicpig-lsh-sampling-efficient-llm/) / cited by

# Who cites «MagicPIG: LSH Sampling for Efficient LLM Generation»

64 papers of our library cite it (of the 141,840 whose bibliographies we read) · 4 with a page here, the most cited first · [← back to «MagicPIG: LSH Sampling for Efficient LLM Generation»](https://md.research.elamur.ai/free/en/papers/chen-2024-magicpig-lsh-sampling-efficient-llm/)

1. [**The Faiss library arXiv:2401.08281**Matthijs Douze, Alexandr Guzhva, Chengqi Deng, et al.*2024 · 442 citations*](https://md.research.elamur.ai/free/en/papers/douze-2024-faiss-library/)
2. **[MInference 1.0: Accelerating Pre-filling for Long-Context LLMs via Dynamic Sparse Attention](https://md.research.elamur.ai/free/en/papers/jiang-2024-minference-1-0-accelerating-pre/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Huiqiang Jiang, Yucheng Li, Chengruidong Zhang, et al.*2024 · 197 citations*
3. [**PyramidKV: Dynamic KV Cache Compression based on Pyramidal Information Funneling arXiv:2406.02069**Zefan Cai, Yichi Zhang, Bofei Gao, et al.*2024 · 151 citations*](https://md.research.elamur.ai/free/en/papers/cai-2024-pyramidkv-dynamic-kv-cache-compression/)
4. [**Native Sparse Attention: Hardware-Aligned and Natively Trainable Sparse Attention arXiv:2502.11089**Jingyang Yuan, Huazuo Gao, Damai Dai, et al.*2025 · 135 citations*](https://md.research.elamur.ai/free/en/papers/yuan-2025-native-sparse-attention-hardware/)

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

- [← back to](https://md.research.elamur.ai/free/en/papers/chen-2024-magicpig-lsh-sampling-efficient-llm/) — MagicPIG: LSH Sampling for Efficient LLM Generation