The research emphasizes the adaptability of shallow feed-forward networks in replicating attention mechanisms. The study employs BLEU scores as the evaluation metric. While successfully repeating the ...

In the Transformer architecture, two main components reign supreme: attention and the FFN. Typically, FFNs occupy roughly two-thirds of the parameter budget, leaving attention with the remaining third ...

Explore the Vision Transformer model, its importance, architecture, building and training process, and its diverse applications in various fields. The Hackett Group Announces Strategic Acquisition of ...

Transformer-based methods are recently popular in vision tasks because of their capability to model global dependencies alone. However, it limits the performance of networks due to the lack of ...

This is accomplished by introducing more convolution operations in the transformer’s two core sections: 1) Instead of the original multi-head attention mechanism, we design a convolutional parameter ...