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cs.LG2026
ScaleSweep: Accurate NVFP4 Post-Training Quantization of LLMs via Block Scale Initialization
Li Lin, Xiaojun Wan
NVFP4 is a recently introduced hardware-supported FP4 format that improves the fidelity of 4-bit quantization through fine-grained block scales. However, existing NVFP4 scale initi…
cs.LG2025
LoaQ: Layer-wise Output Approximation Quantization
Li Lin, Xiaojun Wan
A natural and intuitive idea in model quantization is to approximate each component's quantized output to match its original. Motivated by this idea, most layer-wise post-training…
cs.LG2025
NeUQI: Near-Optimal Uniform Quantization Parameter Initialization for Low-Bit LLMs
Li Lin, Xinyu Hu, Xiaojun Wan
Large language models (LLMs) achieve impressive performance across domains but face significant challenges when deployed on consumer-grade GPUs or personal devices such as laptops,…