Venules
发表于 2025-3-26 21:29:43
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弄脏
发表于 2025-3-27 03:49:52
Predicting Categorial Sememe for English-Chinese Word Pairs via Representations in Explainable Semem the effectiveness of the proposed method. Using this method, we predict categorial sememes for 113,014 new word senses, and the prediction MAP is 85.8%. Further we conduct expert annotations based on prediction results and increase HowNet nearly by 50%. We will publish all the data and code.
prolate
发表于 2025-3-27 07:43:45
Adaptive Transformer for Multilingual Neural Machine Translationf parameter sharing. We evaluate our model on one-to-many and many-to-one translation tasks. Experiments on IWSLT dataset show that our proposed model remarkably outperforms the multilingual baseline model and achieves comparable or even better performance compared with the bilingual model.
松软
发表于 2025-3-27 11:00:08
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秘传
发表于 2025-3-27 15:57:54
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咆哮
发表于 2025-3-27 20:05:03
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wangle
发表于 2025-3-28 00:24:35
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EXTOL
发表于 2025-3-28 05:57:09
0302-9743 ltilinguality; Machine Learning for NLP; Information Extraction and Knowledge Graph; Summarization and Generation; Question Answering; Dialogue Systems; Social Media and Sentiment Analysis; NLP Applications and Text Mining; and Multimodality and Explainability..978-3-030-88479-6978-3-030-88480-2Series ISSN 0302-9743 Series E-ISSN 1611-3349
轻快带来危险
发表于 2025-3-28 08:03:04
Conference proceedings 2021inese Computing, NLPCC 2021, held in Qingdao, China, in October 2021..The 66 full papers, 23 poster papers, and 27 workshop papers presented were carefully reviewed and selected from 446 submissions. They are organized in the following areas: Fundamentals of NLP; Machine Translation and Multilingual
ascend
发表于 2025-3-28 12:45:24
Coreference Resolution: Are the Eliminated Spans Totally Worthless?coreference resolution mainly depend on mention representations, while the rest spans in the text are largely ignored and directly eliminated. In this paper, we aim at investigating whether those eliminated spans are totally worthless, or to what extent they can help improve the performance of coref