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pro vyhledávání: '"Sherborne, A."'
Autor:
Nicholas Brooks, Katherine Barker
This collection of papers follows on from a conference, held in Sherborne in June 2005, marking the thirteen-hundredth anniversary of the founding of the bishopric by Aldhelm of Malmesbury. This volume looks at the work of Aldhelm and the foundation
Autor:
HASSALL, RACHEL
Publikováno v:
The Powys Journal, 2021 Jan 01. 31, 152-168.
Externí odkaz:
https://www.jstor.org/stable/27033273
Akademický článek
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Autor:
Pokorska Marta, Czechowski Marcin
Publikováno v:
Biomedical Human Kinetics, Vol 12, Iss 1, Pp 115-124 (2020)
Study aim: The aim of the study was to evaluate the effectiveness of Shantala massage during the classes conducted using the Developmental Movement method in improving the “with” relationship in healthy children aged 3 to 4 years.
Externí odkaz:
https://doaj.org/article/c216d23703a64ec284d5392cec792f79
Publikováno v:
Pedagogika Przedszkolna i Wczesnoszkolna / Pre-School and Early School Education. 1(19):123-135
Externí odkaz:
https://www.ceeol.com/search/article-detail?id=1084255
Autor:
Strzałkowska-Nowak, Iwona
Publikováno v:
Rozprawy Społeczne / Social Dissertations. 12(4):65-74
Externí odkaz:
https://www.ceeol.com/search/article-detail?id=763374
Autor:
Waymark, Janet
Publikováno v:
Garden History, 2001 Jul 01. 29(1), 64-81.
Externí odkaz:
https://www.jstor.org/stable/1587355
Autor:
Monckton, Linda
Publikováno v:
Architectural History, 2000 Jan 01. 43, 88-112.
Externí odkaz:
https://www.jstor.org/stable/1568687
Autor:
Khalifa, Muhammad, Tan, Yi-Chern, Ahmadian, Arash, Hosking, Tom, Lee, Honglak, Wang, Lu, Üstün, Ahmet, Sherborne, Tom, Gallé, Matthias
Model merging has shown great promise at combining expert models, but the benefit of merging is unclear when merging ``generalist'' models trained on many tasks. We explore merging in the context of large ($\sim100$B) models, by \textit{recycling} ch
Externí odkaz:
http://arxiv.org/abs/2412.04144
Autor:
Na, Clara, Magnusson, Ian, Jha, Ananya Harsh, Sherborne, Tom, Strubell, Emma, Dodge, Jesse, Dasigi, Pradeep
Training data compositions for Large Language Models (LLMs) can significantly affect their downstream performance. However, a thorough data ablation study exploring large sets of candidate data mixtures is typically prohibitively expensive since the
Externí odkaz:
http://arxiv.org/abs/2410.15661