Titlebook: Analysis of Images, Social Networks and Texts; 11th International C Dmitry I. Ignatov,Michael Khachay,Sergey Zagoruyko Conference proceedin

Meager

cardiovascular

https://doi.org/10.1007/978-981-19-8245-3toxification, a relatively new yet practical TST subtask. We work with detoxification in two languages: Russian and English. For both languages, ParaCAIF significantly reduces the toxicity of the generated paraphrases as compared to plain paraphrasers. To the best of our knowledge, it is the first w

eardrum

https://doi.org/10.1057/9781137443649ite, finding that it can be safely reduced. Our experiments are conducted for two models, BERT and RoBERTa, showing the latter to consistently require more data. Fractions probing can be used to analogously investigate other datasets and models.

FLAGR

transient-pain

Alan Brown,Jerry Fishenden,Mark Thompsonapproaches to detecting dialect features, and identified the advantages and disadvantages of each. Ultimately, we developed a unified algorithm that incorporates the best of the approaches considered, it takes a .wav file as input and returns .TextGrid and .eaf files with annotations and detected di

步兵

milligram

archetype

Threatening Expression and Target Identification in Under-Resource Languages Using NLP Techniquestes unrest and harms to the society. Literature describes several forms of the hate speech and it is quite challenging to differentiate between these forms and to design an automated detection system, especially for under-resource languages. In this study, we propose a robust framework for threateni

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vitrectomy