5 papers
Learning Mechanism Underlying NLP Pre-Training and Fine-Tuning
Yarden Tzach, Ronit D. Gross, Ella Koresh +4
Natural language processing (NLP) enables the understanding and generation of meaningful human language, typically using a pre-trained complex architecture on a large dataset to le…
Tiny language models
Ronit D. Gross, Yarden Tzach, Tal Halevi +2
A prominent achievement of natural language processing (NLP) is its ability to understand and generate meaningful human language. This capability relies on complex feedforward tran…
Low-latency vision transformers via large-scale multi-head attention
Ronit D. Gross, Tal Halevi, Ella Koresh +2
The emergence of spontaneous symmetry breaking among a few heads of multi-head attention (MHA) across transformer blocks in classification tasks was recently demonstrated through t…
Unified CNNs and transformers underlying learning mechanism reveals multi-head attention modus vivendi
Ella Koresh, Ronit D. Gross, Yuval Meir +3
Convolutional neural networks (CNNs) evaluate short-range correlations in input images which progress along the layers, whereas vision transformer (ViT) architectures evaluate long…
Advanced deep architecture pruning using single filter performance
Yarden Tzach, Yuval Meir, Ronit D. Gross +3
Pruning the parameters and structure of neural networks reduces the computational complexity, energy consumption, and latency during inference. Recently, a novel underlying mechani…