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Found 21 papers, 2 papers with code
A Simple and Effective Unified Encoder for Document-Level Machine Translation
Most of the existing models for document-level machine translation adopt dual-encoder structures.
Improving Neural Machine Translation with Soft Template Prediction
Although neural machine translation (NMT) has achieved significant progress in recent years, most previous NMT models only depend on the source text to generate translation.
Document Classification for COVID-19 Literature
The global pandemic has made it more important than ever to quickly and accurately retrieve relevant scientific literature for effective consumption by researchers in a wide range of fields.
Syntax-aware Data Augmentation for Neural Machine Translation
Data augmentation is an effective performance enhancement in neural machine translation (NMT) by generating additional bilingual data.
XGPT: Cross-modal Generative Pre-Training for Image Captioning
While many BERT-based cross-modal pre-trained models produce excellent results on downstream understanding tasks like image-text retrieval and VQA, they cannot be applied to generation tasks directly.
Cross-Enhancement Transform Two-Stream 3D ConvNets for Action Recognition
In this way, the enhanced-trained stream and teacher stream are combined to infer actions.
A Novel Task-Oriented Text Corpus in Silent Speech Recognition and its Natural Language Generation Construction Method
In the process of construction, we propose a task-oriented hybrid construction method based on natural language generation algorithm.
Research on the pixel-based and object-oriented methods of urban feature extraction with GF-2 remote-sensing images
During the rapid urbanization construction of China, acquisition of urban geographic information and timely data updating are important and fundamental tasks for the refined management of cities.
Learning Unsupervised Word Mapping by Maximizing Mean Discrepancy
In order to avoid such sophisticated alternate optimization, we propose to learn unsupervised word mapping by directly maximizing the mean discrepancy between the distribution of transferred embedding and target embedding.
Achieving Human Parity on Automatic Chinese to English News Translation
Machine translation has made rapid advances in recent years.
Ranked #3 on
Machine Translation
on WMT 2017 English-Chinese
Sequence-to-Dependency Neural Machine Translation
Nowadays a typical Neural Machine Translation (NMT) model generates translations from left to right as a linear sequence, during which latent syntactic structures of the target sentences are not explicitly concerned.
