大洪水
发表于 2025-3-30 11:48:45
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craving
发表于 2025-3-30 13:15:42
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crutch
发表于 2025-3-30 17:30:08
was the top performing headline generation system at DUC 2004. Topiary-style headlines consist of a number of general topic labels followed by a compressed version of the lead sentence of a news story. The Topiary system uses a statistical learning approach to finding topic labels for headlines, whi
伪造者
发表于 2025-3-30 23:45:08
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吗啡
发表于 2025-3-31 04:54:22
Ricardo R. Gudwint has become pervasive during the COVID-19 pandemic. Previous research [.] has approached this problem with standard classification technology using a set of features that have included linguistic and external variables, among others. In this work, we aim to replicate parts of the study conducted by
天然热喷泉
发表于 2025-3-31 06:31:49
Peter Bøgh Andersenent state-of-the-art systems fail to consider the underlying semantics involved when rating an item. This in turn contributes to many false recommendations. These models hinder the possibility of explaining . or .. In this paper, we develop an approach incorporating the underlying semantics involved
Maximize
发表于 2025-3-31 13:16:25
Carlos Alberto Cocozza Simoni,Maria Cecília Calani Baranaukasdscape of memes, the realm of sarcastic memes holds a unique position with its foundation in irony, mockery, satire, and messages that diverge from literal meanings. Detecting sarcasm in memes is challenging due to the intricate interplay between sarcasm and humor. While prior research has primarily
Radiation
发表于 2025-3-31 14:23:26
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Wernickes-area
发表于 2025-3-31 19:38:08
Pierre-Jean Charrelromote, represent crucial challenges for research and industry. However, the current lack of automatic methods to comprehensively measure or increase viewpoint diversity in search results complicates the understanding and mitigation of such effects. This paper proposes a viewpoint bias metric that e
佛刊
发表于 2025-3-31 21:44:42
Elena Revilla,José Sánchez-Alarcosaper, we provide an overview . the TDT research program from its inception to the third phrase that is now underway. We also discuss our approach to two of the TDT problems in detail. For event clustering (Detection), we show that classic Information Retrieval clustering techniques can be modified s