Кросслингвистическое Обучение

Distributed representations of words have proven extremely useful in numerous natural lan- guage processing tasks. Their appeal is that they can help alleviate data sparsity problems common to supervised learning. …...

Cross-lingual learning has become a popu- lar approach to facilitate the development of resources and tools for low-density lan- guages. Its underlying idea is to make use of existing tools …...

We present the Trip-MAML dataset, a Multi-Lingual dataset of hotel reviews that have been manually annotated at the sentence-level with Multi-Aspect senti- ment labels. This dataset has been built as …...

Cross-Lingual Learning provides a mech- anism to adapt NLP tools available for la- bel rich languages to achieve similar tasks for label-scarce languages. An efficient cross-lingual tool significantly reduces the …...

AbstractThe Universal Dependencies (UD) project was conceived after the substantial recent interest in unifying annotation schemes across languages. With its own annotation principles and abstract inventory for parts of speech, …...

AbstractThis paper presents Prompsit Language Engineering’s submission to the IWSLT 2018 Low Resource Machine Translation task. Our submission is based on cross-lingual learning: a multilingual neural machine translation system was …...

AbstractCombinatory categorial grammars are linguistically motivated and useful for semantic parsing, but costly to acquire in a supervised way and difficult to acquire in an unsupervised way. We propose an …...

AbstractAspect-based sentiment analysis involves the recognition of so called opinion target expressions (OTEs). To automatically extract OTEs, supervised learning algorithms are usually employed which are trained on manually annotated corpora. …...

AbstractAlthough recent developments in neural architectures and pre-trained representations have greatly increased state-of-the-art model performance on fully-supervised semantic role labeling (SRL), the task remains challenging for languages where supervised SRL …...

AbstractUnfortunately, offensive language in social media is a common phenomenon nowadays. It harms many people and vulnerable groups. Therefore, automated detection of offensive language is in high demand and it …...

AbstractLarge pretrained multilingual models, trained on dozens of languages, have delivered promising results due to cross-lingual learning capabilities on a variety of language tasks. Further adapting these models to specific …...

AbstractRecent research in cross-lingual learning has found that combining large-scale pretrained multilingual language models with machine translation can yield good performance. We explore this idea for cross-lingual event extraction with …...