7 citations · 10 across the 9 of their papers we have counts for
3 papers · 1 filter
Affine-Scaled Attention: Towards Flexible and Stable Transformer Attention
Jeongin Bae, Baeseong Park, Gunho Park +7
Transformer attention is typically implemented using softmax normalization, which enforces attention weights with unit sum normalization. While effective in many settings, this con…
Unifying Uniform and Binary-coding Quantization for Accurate Compression of Large Language Models
Seungcheol Park, Jeongin Bae, Beomseok Kwon +5
How can we quantize large language models while preserving accuracy? Quantization is essential for deploying large language models (LLMs) efficiently. Binary-coding quantization (B…
HyperCLOVA X Technical Report
Kang Min Yoo, Jaegeun Han, Sookyo In +393
We introduce HyperCLOVA X, a family of large language models (LLMs) tailored to the Korean language and culture, along with competitive capabilities in English, math, and coding. H…