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H. Mak

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HiFloat4 Format for Language Model Pre-training on Ascend NPUs

It is argued that numerical format design is itself a first-class lever for stable FP4 training, and the first systematic study of FP4 LLM pretraining on energy-efficient Huawei Ascend NPUs is presented.

Mehran Taghian, Yun Peng, Xing Huang et al. · 3 citations
Preprint Aug 2026

Activation Outliers Matter: Robust Recovery for Quantized Multimodal LLMs

This work proposes Residual Fallback Quantization (RFQ), a lightweight activation reconstruction framework that supplements the primary ulta-low-bit activation representation with an auxiliary quantized residual pathway that improves activation fidelity while preserving the efficiency advantages of ultra-low-bit comput...

Tanzila Rahman, Mehran Taghian Jazi, Yunke Peng et al. · 0 citations

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