无能力之人
发表于 2025-3-25 07:10:42
Oleksandra Pallah,Nadiya Boyko decrease navigation effort, but helped to draw the readers’ attention towards highlighted parts and decreased the average time spent on pages. . We explored and evaluated the approach of visualizing other readers’ attention focus to help support new readers. Our results include interesting findings
Vulvodynia
发表于 2025-3-25 09:48:59
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讨人喜欢
发表于 2025-3-25 15:13:19
Elena Ermolenko,Irina Koroleva,Alexander Suvorovoptimise the resultant CNL. We also challenge the concept of a CNL being a one-dimensional static language, and demonstrate that our optimal-constraint process results in a CNL that can adapt to a changing domain while maintaining its expressiveness.
Regurgitation
发表于 2025-3-25 16:09:14
Tamara Meleshko,Nadiya Boykod . are among the most commonly discussed issues. We also list 20 causes, 23 effects, and 59 solutions for the mined issues. Examples of causes for RE issues are . and .. Examples of the effects of RE issues are . and .. Solutions encompass practices such as . and using .. . This work organizes the
吹气
发表于 2025-3-25 20:30:09
Ganna Tolstanova,Iryna Akulenko,Tetiiana Serhiichuk,Taisa Dovbynchuk,Natalia Stepanovahanges. To support engineers in making informed decisions during the design, development, and evolution of a system, we propose a framework to collect and maintain intentionality in an efficient and effortless way. To define intentionality, disambiguate it from its u
协议
发表于 2025-3-26 02:07:08
Rostyslav V. Bubnov,Lidiia P. Babenko,Liudmyla M. Lazarenko,Victoria V. Mokrozub,Mykola Spivakhanges. To support engineers in making informed decisions during the design, development, and evolution of a system, we propose a framework to collect and maintain intentionality in an efficient and effortless way. To define intentionality, disambiguate it from its u
chemoprevention
发表于 2025-3-26 06:55:04
Liudmyla Lazarenko,Oleksandra Melnykova,Lidiia Babenko,Rostyslav Bubnov,Tetyana Beregova,Tetyana Falhow that the transformer-based BERT classifier performs the best, with an average F1 score of 0.82 and 0.87 on industrial and public datasets, respectively. Our results also confirm that few-shot classifiers can achieve comparable results with an average F1 score of 0.76 on significantly lower sampl
我正派
发表于 2025-3-26 09:11:34
Jack C. Yu,Hesam Khodadadi,Évila Lopes Salles,Sahar Emami Naeini,Edie Threlkeld,Bidhan Bhandari,Mohaess this challenge, this paper proposes a novel approach that employs the Zero-Shot Learning (ZSL) technique to perform requirements classification. We build several classification models using ZSL. We focus on the classification task because many RE tasks can be solved as classification problems by
钳子
发表于 2025-3-26 13:48:33
Advances in Predictive, Preventive and Personalised Medicinehttp://image.papertrans.cn/m/image/633111.jpg
Apogee
发表于 2025-3-26 18:02:43
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