12 citations · 32 across the 8 of their papers we have counts for
5 papers · 1 filter
RuCLIP -- new models and experiments: a technical report
Alex Shonenkov, Andrey Kuznetsov, Denis Dimitrov +10
In the report we propose six new implementations of ruCLIP model trained on our 240M pairs. The accuracy results are compared with original CLIP model with Ru-En translation (OPUS-…
Survey on Large Scale Neural Network Training
Julia Gusak, Daria Cherniuk, Alena Shilova +8
Modern Deep Neural Networks (DNNs) require significant memory to store weight, activations, and other intermediate tensors during training. Hence, many models do not fit one GPU de…
A new face swap method for image and video domains: a technical report
Daniil Chesakov, Anastasia Maltseva, Alexander Groshev +2
Deep fake technology became a hot field of research in the last few years. Researchers investigate sophisticated Generative Adversarial Networks (GAN), autoencoders, and other appr…
Few-Bit Backward: Quantized Gradients of Activation Functions for Memory Footprint Reduction
Georgii Novikov, Daniel Bershatsky, Julia Gusak +3
Memory footprint is one of the main limiting factors for large neural network training. In backpropagation, one needs to store the input to each operation in the computational grap…
Emojich -- zero-shot emoji generation using Russian language: a technical report
Alex Shonenkov, Daria Bakshandaeva, Denis Dimitrov +1
This technical report presents a text-to-image neural network "Emojich" that generates emojis using captions in Russian language as a condition. We aim to keep the generalization a…