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pro vyhledávání: '"Malmi"'
Autor:
Hewidy, Hossam1 (AUTHOR) hossam.hewidy@aalto.fi, Lilius, Johanna1 (AUTHOR)
Publikováno v:
European Planning Studies. Feb 2022, Vol. 30 Issue 2, p336-358. 23p. 7 Color Photographs, 1 Diagram, 3 Charts, 1 Graph.
Publikováno v:
In Transportation Geotechnics January 2023 38
Autor:
Schultz, John, Adamek, Jakub, Jusup, Matej, Lanctot, Marc, Kaisers, Michael, Perrin, Sarah, Hennes, Daniel, Shar, Jeremy, Lewis, Cannada, Ruoss, Anian, Zahavy, Tom, Veličković, Petar, Prince, Laurel, Singh, Satinder, Malmi, Eric, Tomašev, Nenad
While large language models perform well on a range of complex tasks (e.g., text generation, question answering, summarization), robust multi-step planning and reasoning remains a considerable challenge for them. In this paper we show that search-bas
Externí odkaz:
http://arxiv.org/abs/2412.12119
Akademický článek
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Akademický článek
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Computing education widely applies general learning theories and pedagogical practices. However, computing also includes specific disciplinary knowledge and skills, e.g., programming and software development methods, for which there has been a long h
Externí odkaz:
http://arxiv.org/abs/2409.12245
Local stresses in a tissue, a collective property, regulate cell division and apoptosis. In turn, cell growth and division induce active stresses in the tissue. As a consequence, there is a feedback between cell growth and local stresses. However, ho
Externí odkaz:
http://arxiv.org/abs/2405.01960
Publikováno v:
Economica (1585-6216). 2015, Vol. 8 Issue 4.2, p249-256. 8p.
Publikováno v:
Phys. Rev. A 109, 062412 (2024)
In recent years, informationally complete measurements have attracted considerable attention, especially in the context of classical shadows. In the particular case of informationally over-complete measurements, for which the number of possible outco
Externí odkaz:
http://arxiv.org/abs/2401.18049
The success of reinforcement learning from human feedback (RLHF) in language model alignment is strongly dependent on the quality of the underlying reward model. In this paper, we present a novel approach to improve reward model quality by generating
Externí odkaz:
http://arxiv.org/abs/2401.12086