Inelasticity
发表于 2025-3-23 11:56:12
Zaixiang Zheng,Shujian Huang,Xin-Yu Dai,Jiajun Chenly consisted of, not so long ago. But secondlyand of greater interest, the geometrie setting rather quickly suggested new methods of attacking synthesis which have proved to be intuitive and economical; they are also easily reduced to matrix arith metic as soonas you want to compute. The essence of
刚毅
发表于 2025-3-23 16:17:52
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CHURL
发表于 2025-3-23 18:39:42
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鄙视
发表于 2025-3-24 00:21:22
Bojie Hu,Ambyer Han,Shen Huangisted of, around fifteen years ago. But secondly and of greater interest, the geometric setting rather quickly sug gested new methods of attacking synthesis which have proved to be intuitive and economical; they are also easily reduced to matrix arithmetic as soon as you want to compute. The essenc
archetype
发表于 2025-3-24 02:23:43
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条约
发表于 2025-3-24 09:38:58
A Grammatical Analysis on Machine Translation Errors,pose to unravel causes leading to these errors. As illustrated with examples, clause complex presents different grammatical features from clause and the structural differences between Chinese and English at clause-complex level are the fundamental source of machine translation errors. This research,
Entrancing
发表于 2025-3-24 12:18:41
RST Discourse Parsing with Tree-Structured Neural Networks,l discourse parsing is notoriously difficult for the long distance of discourse and deep structures of discourse trees. In this paper, we build a tree-structured neural network for RST discourse parsing. We also introduce two tracking LSTMs to store long-distance information of a document to strengt
令人发腻
发表于 2025-3-24 18:34:35
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FUSE
发表于 2025-3-24 21:22:07
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Interim
发表于 2025-3-25 02:00:52
Cross-Lingual Semantic Textual Similarity Modeling Using Neural Networks,on leveraging traditional NLP features (e.g., alignment features, syntactic features) to evaluate the semantic similarity of sentences. In this paper, we only use word embedding as basic features without any handcrafted features and build a model which is able to capture local and global semantic in