English to Spanish Translation. Overview Machine translation using a sequence-to-sequence (seq2seq) encoder-decoder model has revolutionized the field of language translation. By leveraging the power ...

This is a repository for an end-to-end Machine Translation project, which uses a neural network trained on a small dataset of English and French text. Written as part of a Udacity project, the encoder ...

Encoder-Decoder-Reconstructor. Figure 3: The attention layer in Example 1 : Improvement in under-translation. Encoder-Decoder-Reconstructor. Figure 4: The attention layer in Example 2 : Improvement in ...

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, ...

The main purpose of multimodal machine translation is to improve the quality of translation results by taking the corresponding visual context as an additional input. Recently many studies in neural ...

Paper topics cover a range of subjects, including: encoder-decoder frameworks, natural language generation, knowledge neurons, extractive text abstracts, pre-trained language models, zero-shot neural ...

The main purpose of multimodal machine translation (MMT) is to improve the quality of translation results by taking the corresponding visual context as an additional input. Recently many studies in ...