An Encoder-Decoder model is a fundamental architecture in the field of deep learning and natural language processing (NLP). It's widely used for a variety of tasks, including machine translation, text ...

Large language models (LLMs) have changed the game for machine translation (MT). LLMs vary in architecture, ranging from decoder-only designs to encoder-decoder frameworks. Encoder-decoder models, ...

GPT-like transformer model consisting of an encoder and a decoder for various natural language processing tasks, including text classification and language modeling. nlp encoder-decoder-model ...

The Mu small language model enables an AI agent to take action on hundreds of system settings. It’s now in preview for some ...

End-to-end (E2E) models, including the attention-based encoder-decoder (AED) models, have achieved promising performance on the automatic speech recognition (ASR) task. However, the supervised ...

Decoder-only models. In the last few years, large neural networks have achieved impressive results across a wide range of tasks. Models like BERT and T5 are trained with an encoder only or ...

In this article, we are going to see how we can remove noise from the image data using an encoder-decoder model. Having clear and processed images or videos is very important in any computer vision ...

This research paper introduces an innovative AI coaching approach by integrating vision-encoder-decoder models. The feasibility of this method is demonstrated using a Vision Transformer as the encoder ...