Titlebook: Artificial Intelligence and Natural Language; 11th Conference, AIN Valentin Malykh,Andrey Filchenkov Conference proceedings 2022 The Editor

Carbon-Monoxide

https://doi.org/10.1007/978-3-658-44688-8the dataset, metrics, and baselines used for the Biomedical Russian-English Machine Translation competition. We describe dataset collection and markup along with baseline development and participants’ models. The collected dataset is available by the link ..

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,WikiMulti: A Corpus for?Cross-Lingual Summarization,uce WikiMulti - a new dataset for cross-lingual summarization based on Wikipedia articles in 15 languages. As a set of baselines for further studies, we evaluate the performance of existing cross-lingual abstractive summarization methods on our dataset. We make our dataset publicly available here: ..

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,Findings of?Biomedical Russian to?English Machine Translation Competition,the dataset, metrics, and baselines used for the Biomedical Russian-English Machine Translation competition. We describe dataset collection and markup along with baseline development and participants’ models. The collected dataset is available by the link ..

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暫停,間歇

,Development of?Folklore Motif Classifier Using Limited Data,nt in the training set. Various ways of vectorizing texts and various models were tested. Evaluation of the results of the classifiers’ work allows us to assert that the developed classifier can correlate texts with motifs with sufficient accuracy.

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