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This study investigates language models' generative capabilities in tool-use dialogs. We categorize the models' outputs in tool-use dialogs into four distinct types: Tool Call, Answer Completion, Slot Question, and Relevance Detection, which serve as
Externí odkaz:
http://arxiv.org/abs/2411.14054
Autor:
Oh, Shinhyeok, Lee, Dongyub, Whang, Taesun, Park, IlNam, Seo, Gaeun, Kim, EungGyun, Kim, Harksoo
Existing works for aspect-based sentiment analysis (ABSA) have adopted a unified approach, which allows the interactive relations among subtasks. However, we observe that these methods tend to predict polarities based on the literal meaning of aspect
Externí odkaz:
http://arxiv.org/abs/2106.03806
Autor:
Seo, Gaeun1 (AUTHOR) gaeunseo@gmail.com, Ahn, Joonkil2 (AUTHOR), Huang, Wen-Hao2 (AUTHOR), Makela, Julia P.2 (AUTHOR), Yeo, HyeJin T.2 (AUTHOR)
Publikováno v:
Journal of Career Development. Dec2021, Vol. 48 Issue 6, p957-972. 16p.
Autor:
Han, Seung-hyun1 (AUTHOR) han84@illinois.edu, Seo, Gaeun2 (AUTHOR), Li, Jessica2 (AUTHOR), Yoon, Seung Won3 (AUTHOR)
Publikováno v:
Human Resource Development International. Apr2016, Vol. 19 Issue 2, p98-115. 18p. 1 Diagram, 4 Charts.
Akademický článek
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Publikováno v:
New Horizons in Adult Education & Human Resource Development; Fall2017, Vol. 29 Issue 4, p20-34, 15p
Publikováno v:
Journal of Workplace Learning; 2016, Vol. 28 Issue 3, p130-149, 20p