Therefore, the workload of transformer-based text generation is severely memory-bound, making the external memory bandwidth system bottleneck. In this paper, we propose a subarray-level ...

Run 🤗 Transformers directly in your browser, with no need for a server! Transformers.js is designed to be functionally equivalent to Hugging Face's transformers python library, meaning you can run ...

Adeel evaluated his adapted transformer architecture in a series of learning, computer vision and language processing tasks. The results of these tests were highly promising, highlighting the promise ...

This review synthesizes recent progress in applying autoencoders and vision transformers for unsupervised signal analysis, focusing on their architectures, applications, and emerging trends. We ...

The architecture of the model is shown in Figure 5. Figure 5. Model architecture diagram of the deep convolutional autoencoder. The input to the model is a 9 × 24 matrix, where 9 represents the 9 ...

we present an adaptive weighted Transformer, with the weights guided by a variational autoencoder (VAE), thereby enhancing the generalization and robustness of the model. The SGA and VAET are ...