1919 papers with code • 0 benchmarks • 0 datasets
The dominant sequence transduction models are based on complex recurrent or convolutional neural networks in an encoder-decoder configuration.
Ranked #2 on Multimodal Machine Translation on Multi30K (BLUE (DE-EN) metric)
We therefore propose Cross-View Training (CVT), a semi-supervised learning algorithm that improves the representations of a Bi-LSTM sentence encoder using a mix of labeled and unlabeled data.
Ranked #1 on CCG Supertagging on CCGbank
Several mechanisms to focus attention of a neural network on selected parts of its input or memory have been used successfully in deep learning models in recent years.
Ranked #48 on Machine Translation on WMT2014 English-French
Dictionaries and phrase tables are the basis of modern statistical machine translation systems.
Automatically describing the content of an image is a fundamental problem in artificial intelligence that connects computer vision and natural language processing.
Image-to-image translation is a class of vision and graphics problems where the goal is to learn the mapping between an input image and an output image using a training set of aligned image pairs.
Ranked #1 on Image-to-Image Translation on photo2vangogh (Frechet Inception Distance metric)
We investigate conditional adversarial networks as a general-purpose solution to image-to-image translation problems.
Ranked #1 on Image-to-Image Translation on Aerial-to-Map
The recent "Text-to-Text Transfer Transformer" (T5) leveraged a unified text-to-text format and scale to attain state-of-the-art results on a wide variety of English-language NLP tasks.
Ranked #2 on Reading Comprehension on MuSeRC
Existing work in translation demonstrated the potential of massively multilingual machine translation by training a single model able to translate between any pair of languages.
We introduce fairseq S2T, a fairseq extension for speech-to-text (S2T) modeling tasks such as end-to-end speech recognition and speech-to-text translation.
Ranked #8 on Speech-to-Text Translation on MuST-C EN->DE