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Dwaipayan Haldar

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#machine learning Preprint Oct 2026

SpectrumQuant: Spectrum Alignment for LLM Quantization

Orthogonal transforms have emerged as an effective tool for low-bit quantization of large language models (LLMs), as they reshape activation distributions without changing the underlying model function. Existing approaches typically rely either on fixed data-agnostic transforms, such as Hadamard rotations, or on calibr...

Dwaipayan Haldar, I. Patra, Azhar Yousuf et al. · 0 citations