Монотілдік модельдер

This work shows how to improve state-of-the-art monolingual natural language processing models using unannotated bilingual text. We build a mul- tiview learning objective that enforces agreement between monolingual and bilingual …...

Neural machine translation (NMT) systems have recently achieved re- sults comparable to the state of the art on a few translation tasks, including English→French and English→German. The main purpose of …...

We introduce polyglot language models, re- current neural network models trained to pre- dict symbol sequences in many different lan- guages using shared representations of sym- bols and conditioning on …...

AbstractComplex Word Identification (CWI) is the task of identifying which words or phrases in a sentence are difficult to understand by a target audience. The latest CWI Shared Task released …...

AbstractIn this paper, we aim at improving Czech sentiment with transformer-based models and their multilingual versions. More concretely, we study the task of polarity detection for the Czech language on …...

AbstractLemmatization aims to reduce the sparse data problem by relating the inflected forms of a word to its dictionary form. Most prior work on ML based lemmatization has focused on …...

AbstractIn order to preserve word-order information in a non-autoregressive setting, transformer architectures tend to include positional knowledge, by (for instance) adding positional encodings to token embeddings. Several modifications have been …...

AbstractTransfer learning based on pretraining language models on a large amount of raw data has become a new norm to reach state-of-the-art performance in NLP. Still, it remains unclear how …...

AbstractRecent studies in cross-lingual learning using multilingual models have cast doubt on the previous hypothesis that shared vocabulary and joint pre-training are the keys to cross-lingual generalization. We introduce a …...

AbstractHate speech is a global phenomenon, but most hate speech datasets so far focus on English-language content. This hinders the development of more effective hate speech detection models in hundreds …...

AbstractThe business world has changed due to the 21st century economy, where borders have melted and trades became free. Nowadays,competition is no longer only at the local market level but …...

AbstractWe report our participation in the SemEval-2023 shared task on propaganda detection and describe our solutions with pre-trained models and their ensembles. For Subtask 1 (News Genre Categorisation), we report …...

AbstractThis paper describes the participation of team QUST in the SemEval2023 task3. The monolingual models are first evaluated with the under-sampling of the majority classes in the early stage of …...

AbstractNamed Entity Recognition is a key Natural Language Processing task whose performance is sensitive to choice of genre and language. A unified NER model across multiple genres and languages is …...

AbstractThis paper presents our submission to the WebNLG Challenge 2023 for generating text in several low-resource languages from RDF-triples. Our submission focuses on using machine translation for generating texts in …...