Zobrazeno 1 - 10
of 8 738
pro vyhledávání: '"Steinfeld, A"'
Architects adopt visual scripting and parametric design tools to explore more expansive design spaces (Coates, 2010), refine their thinking about the geometric logic of their design (Woodbury, 2010), and overcome conventional software limitations (Bu
Externí odkaz:
http://arxiv.org/abs/2411.14485
Autor:
Alshehri, Azzah, Bürger, Jan, Chopra, Saransh, Eich, Niclas, Eppelt, Jonas, Erdmann, Martin, Eschle, Jonas, Fackeldey, Peter, Farkas, Maté, Feickert, Matthew, Fillinger, Tristan, Fischer, Benjamin, Gerlach, Lino Oscar, Hartmann, Nikolai, Heidelbach, Alexander, Held, Alexander, Ivanov, Marian I, Molina, Josué, Nikitenko, Yaroslav, Osborne, Ianna, Padulano, Vincenzo Eduardo, Pivarski, Jim, Praz, Cyrille, Rieger, Marcel, Rodrigues, Eduardo, Shadura, Oksana, Smieško, Juraj, Stark, Giordon Holtsberg, Steinfeld, Judith, Warkentin, Angela
The second PyHEP.dev workshop, part of the "Python in HEP Developers" series organized by the HEP Software Foundation (HSF), took place in Aachen, Germany, from August 26 to 30, 2024. This gathering brought together nearly 30 Python package developer
Externí odkaz:
http://arxiv.org/abs/2410.02112
With more robots being deployed in the world, users will likely interact with multiple robots sequentially when receiving services. In this paper, we describe an exploratory field study in which unsuspecting participants experienced a ``person transf
Externí odkaz:
http://arxiv.org/abs/2406.06904
In this work, we aim to improve transparency and efficacy in human-robot collaboration by developing machine teaching algorithms suitable for groups with varied learning capabilities. While previous approaches focused on tailored approaches for teach
Externí odkaz:
http://arxiv.org/abs/2404.15472
When extreme weather events affect large areas, their regional to sub-continental spatial scale is important for their impacts. We propose a novel machine learning (ML) framework that integrates spatial extreme-value theory to model weather extremes
Externí odkaz:
http://arxiv.org/abs/2401.12195
Social navigation and pedestrian behavior research has shifted towards machine learning-based methods and converged on the topic of modeling inter-pedestrian interactions and pedestrian-robot interactions. For this, large-scale datasets that contain
Externí odkaz:
http://arxiv.org/abs/2309.17187
This paper explores the integration of two AI subdisciplines employed in the development of artificial agents that exhibit intelligent behavior: Large Language Models (LLMs) and Cognitive Architectures (CAs). We present three integration approaches,
Externí odkaz:
http://arxiv.org/abs/2308.09830
Publikováno v:
Cityscape, 2024 Jan 01. 26(1), 415-430.
Externí odkaz:
https://www.jstor.org/stable/48766092
Typical black-box optimization approaches in robotics focus on learning from metric scores. However, that is not always possible, as not all developers have ground truth available. Learning appropriate robot behavior in human-centric contexts often r
Externí odkaz:
http://arxiv.org/abs/2308.04571
Autor:
Jafarbeiki, Sara, Sakzad, Amin, Steinfeld, Ron, Kermanshahi, Shabnam Kasra, Thapa, Chandra, Kume, Yuki
In this paper, we introduce ACE, a consent-embedded searchable encryption scheme. ACE enables dynamic consent management by supporting the physical deletion of associated data at the time of consent revocation. This ensures instant real deletion of d
Externí odkaz:
http://arxiv.org/abs/2307.12285