描述
发表于 2025-3-28 16:07:44
https://doi.org/10.1007/978-3-8348-9370-3s. ELMo and BERT architectures are compared on the task of ranking Russian words according to the degree of their semantic change over time. We use several methods for aggregation of contextualized embeddings from these architectures and evaluate their performance. Finally, we compare unsupervised and supervised techniques in this task.
开玩笑
发表于 2025-3-28 22:35:59
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Allege
发表于 2025-3-29 01:52:19
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groggy
发表于 2025-3-29 03:52:30
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indignant
发表于 2025-3-29 08:00:57
Programmierbare Logikbausteine,ads of high-quality media that publishes news in accordance with the classical model. We prove dataset eligibility for training by building an abstractive summarization framework based on pre-trained language models and comparing summarization results with extractive baselines.
modish
发表于 2025-3-29 14:59:34
https://doi.org/10.1007/978-3-8348-9038-2l word representations outperform previously proposed feature-based models for discourse relation classification. By ensembling both methods, we are able to further improve the performance of the discourse relation classification achieving the new state of the art for Russian.
迅速飞过
发表于 2025-3-29 18:58:49
Abstractive Summarization of Russian News Learning on Quality Mediaads of high-quality media that publishes news in accordance with the classical model. We prove dataset eligibility for training by building an abstractive summarization framework based on pre-trained language models and comparing summarization results with extractive baselines.
machination
发表于 2025-3-29 20:42:57
RST Discourse Parser for Russian: An Experimental Study of Deep Learning Modelsl word representations outperform previously proposed feature-based models for discourse relation classification. By ensembling both methods, we are able to further improve the performance of the discourse relation classification achieving the new state of the art for Russian.
Heretical
发表于 2025-3-30 01:52:24
Conference proceedings 2021ers are organized in topical sections as follows: invited papers; natural language processing; computer vision; social network analysis; data analysis and machine learning; theoretical machine learning and optimization; and process mining. .. .
不易燃
发表于 2025-3-30 07:22:12
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