They excel at processing and generating text by leveraging intricate mechanisms like self-attention and positional encoding. In this blog, we’ll break down how Transformers generate tokens ...

Attention mechanisms are at the core of transformer architectures, enabling models to capture relationships within and across sequences. Two critical attention types are Self-Attention and ...

Modern systems for automatic speech recognition, including the RNN-Transducer and Attention-based Encoder-Decoder (AED), are designed so ... We discover that the transformer-based encoder adopted in ...

A novel technique of FER that integrates an attention-guided Swin Transformer-based encoder-decoder model is furnished here. The proposed model leverages channel attention and positional attention ...

We propose a method for anomaly localization in industrial images using Transformer Encoder-Decoder Mask Reconstruction. The self-attention mechanism of the Transformer enables better attention to ...