Hy-MT2 is a new family of fast multilingual translation models that claim to outperform several open-source LLMs and commercial APIs across diverse evaluation settings while supporting efficient on-device deployment.
Sherry: Hardware-efficient 1.25-bit ternary quantization via fine-grained sparsification
2 Pith papers cite this work. Polarity classification is still indexing.
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2026 2verdicts
UNVERDICTED 2representative citing papers
DuQuant++ adapts outlier-aware fine-grained rotation to MXFP4 by matching block size to the 32-element microscaling group, enabling a single rotation that smooths distributions and achieves SOTA performance on LLaMA-3 with lower cost.
citing papers explorer
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Hy-MT2: A Family of Fast, Efficient and Powerful Multilingual Translation Models in the Wild
Hy-MT2 is a new family of fast multilingual translation models that claim to outperform several open-source LLMs and commercial APIs across diverse evaluation settings while supporting efficient on-device deployment.
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DuQuant++: Fine-grained Rotation Enhances Microscaling FP4 Quantization
DuQuant++ adapts outlier-aware fine-grained rotation to MXFP4 by matching block size to the 32-element microscaling group, enabling a single rotation that smooths distributions and achieves SOTA performance on LLaMA-3 with lower cost.