---
title: "Who cites The case for 4-bit precision: k-bit Inference…"
description: "95 papers of the Elamur Research library cite «The case for 4-bit precision: k-bit Inference Scaling Laws», found in their bibliographies; the most cited…"
canonical: "https://research.elamur.ai/free/en/papers/dettmers-2022-case-4-bit-precision-k/cited-by/"
---
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# Who cites «The case for 4-bit precision: k-bit Inference Scaling Laws»

95 papers of our library cite it (of the 140,884 whose bibliographies we read) · 7 with a page here, the most cited first · [← the paper](https://md.research.elamur.ai/free/en/papers/dettmers-2022-case-4-bit-precision-k/)

1. [**A Survey of Large Language Models**Wayne Xin Zhao, Kun Zhou, Junyi Li, et al.*2023 · 2,847 citations*](https://md.research.elamur.ai/free/en/papers/zhao-2023-survey-large-language-models/)
2. [**FlexGen: High-Throughput Generative Inference of Large Language Models with a Single GPU**Ying Sheng, Lianmin Zheng, Binhang Yuan, et al.*2023 · 399 citations*](https://md.research.elamur.ai/free/en/papers/sheng-2023-flexgen-high-throughput-generative-inference/)
3. [**OmniQuant: Omnidirectionally Calibrated Quantization for Large Language Models**Wenqi Shao, Mengzhao Chen, Zhaoyang Zhang, et al.*2023 · 193 citations*](https://md.research.elamur.ai/free/en/papers/shao-2023-omniquant-omnidirectionally-calibrated-quantization-large/)
4. [**Moshi: a speech-text foundation model for real-time dialogue**Alexandre Defossez, Laurent Mazare, Manu Orsini, et al.*2024 · 154 citations*](https://md.research.elamur.ai/free/en/papers/defossez-2024-moshi-speech-text-foundation-model/)
5. [**Pretraining Language Models with Human Preferences**Tomasz Korbak, Kejian Shi, Angelica Chen, et al.*2023 · 117 citations*](https://md.research.elamur.ai/free/en/papers/korbak-2023-pretraining-language-models-human-preferences/)
6. [**QuIP#: Even Better LLM Quantization with Hadamard Incoherence and Lattice Codebooks**Albert Tseng, Jerry Chee, Qingyao Sun, et al.*2024 · 116 citations*](https://md.research.elamur.ai/free/en/papers/tseng-2024-quip-even-better-llm-quantization/)
7. [**Scaling Laws for Generative Mixed-Modal Language Models**Armen Aghajanyan, Lili Yu, Alexis Conneau, et al.*2023 · 39 citations*](https://md.research.elamur.ai/free/en/papers/aghajanyan-2023-scaling-laws-generative-mixed-modal/)

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

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