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References (8)

[1]
ButterflyQuant: Ultra-low-bit LLM Quantization through Learnable Orthogonal Butterfly Transforms
2025Bingxin Xu, Zhen Dong et al.
[2]
VPTQ: Extreme Low-bit Vector Post-Training Quantization for Large Language Models
2024Yifei Liu, Jicheng Wen et al.
[3]
QTIP: Quantization with Trellises and Incoherence Processing
2024Albert Tseng, Qingyao Sun et al.
[4]
SpinQuant: LLM quantization with learned rotations
2024Zechun Liu, Changsheng Zhao et al.
[5]
QuaRot: Outlier-Free 4-Bit Inference in Rotated LLMs
2024Saleh Ashkboos, Amirkeivan Mohtashami et al.
[6]
QuIP#: Even Better LLM Quantization with Hadamard Incoherence and Lattice Codebooks
2024Albert Tseng, Jerry Chee et al.
[7]
CulturaX: A Cleaned, Enormous, and Multilingual Dataset for Large Language Models in 167 Languages
2023Thuat Nguyen, C. Nguyen et al.
[8]
GPTQ: Accurate Post-Training Quantization for Generative Pre-trained Transformers
2022Elias Frantar, Saleh Ashkboos et al.

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