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Titlebook: Natural Language Processing and Information Systems; 29th International C Amon Rapp,Luigi Di Caro,Vijayan Sugumaran Conference proceedings

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樓主: osteomalacia
41#
發(fā)表于 2025-3-28 14:55:01 | 只看該作者
Maria Lysyuk,Mikhail Salnikov,Pavel Braslavski,Alexander Panchenkoote to Bill Merwin to ask whether he was currently working on something that might be suitable for the collection. At the same time I mentioned an item which had appeared in . (No. 9, 1982, Dallas). This included a short introduction by Michael Gormon, ‘W.S. Merwin Translator Poet’, with accompanyin
42#
發(fā)表于 2025-3-28 19:18:06 | 只看該作者
43#
發(fā)表于 2025-3-29 01:06:42 | 只看該作者
44#
發(fā)表于 2025-3-29 05:39:10 | 只看該作者
Amit Maraj,Miguel Vargas Martin,Masoud Makrehchiactively seeks to avoid. Both the authenticising subtitles discussed in the previous chapter and conventional post- subtitles depend for their effect on their almost subliminal impact. According to Donald Richie ‘a(chǎn)ny oddity, any term too heightened, as well as any mistake, calls attention to this wr
45#
發(fā)表于 2025-3-29 09:48:44 | 只看該作者
46#
發(fā)表于 2025-3-29 13:12:25 | 只看該作者
47#
發(fā)表于 2025-3-29 19:29:59 | 只看該作者
Beimnet Zenebe,Solomon Gizaw,Yalemisew Abgazfunctional programming and program transformation. The first part presents two algorithms which generate iterative programs from algebra-based query specifications. While the first algorithm is based on the transformation of recursive programs, the second uses functional expressions to generate the
48#
發(fā)表于 2025-3-29 21:41:30 | 只看該作者
Joshua Berger,Jonathan Ko?,Markos Stamatakis,Anett Hoppe,Ralph Ewerth,Christian Wartenafunctional programming and program transformation. The first part presents two algorithms which generate iterative programs from algebra-based query specifications. While the first algorithm is based on the transformation of recursive programs, the second uses functional expressions to generate the
49#
發(fā)表于 2025-3-30 01:19:41 | 只看該作者
50#
發(fā)表于 2025-3-30 07:35:26 | 只看該作者
,Large-Scale Language Models for?Sarcasm Detection with?Data Augmentation,igh-quality and abundant data is usually not readily available in practice, which hinders the success of?many deep learning projects. Even though there are already several?data augmentation techniques available to expand the dataset,?the critical concern still remains: will the augmented data be sui
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