1 citations · 2 across the 3 of their papers we have counts for
3 papers
Quantization of Large Language Models with an Overdetermined Basis
Daniil Merkulov, Daria Cherniuk, Alexander Rudikov +4
In this paper, we introduce an algorithm for data quantization based on the principles of Kashin representation. This approach hinges on decomposing any given vector, matrix, or te…
LoTR: Low Tensor Rank Weight Adaptation
Daniel Bershatsky, Daria Cherniuk, Talgat Daulbaev +2
In this paper we generalize and extend an idea of low-rank adaptation (LoRA) of large language models (LLMs) based on Transformer architecture. Widely used LoRA-like methods of fin…
Quantization Aware Factorization for Deep Neural Network Compression
Daria Cherniuk, Stanislav Abukhovich, Anh-Huy Phan +3
Tensor decomposition of convolutional and fully-connected layers is an effective way to reduce parameters and FLOP in neural networks. Due to memory and power consumption limitatio…