Zobrazeno 1 - 10
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pro vyhledávání: '"Heiman AS"'
Medical vision-language model models often struggle with generating accurate quantitative measurements in radiology reports, leading to hallucinations that undermine clinical reliability. We introduce FactCheXcker, a modular framework that de-halluci
Externí odkaz:
http://arxiv.org/abs/2411.18672
The rapid advancement of medical technology has led to an exponential increase in multi-modal medical data, including imaging, genomics, and electronic health records (EHRs). Graph neural networks (GNNs) have been widely used to represent this data d
Externí odkaz:
http://arxiv.org/abs/2410.00944
In pioneering work from 2019, Barcel\'o and coauthors identified logics that precisely match the expressive power of constant iteration-depth graph neural networks (GNNs) relative to properties definable in first-order logic. In this article, we give
Externí odkaz:
http://arxiv.org/abs/2405.14606
Autor:
Nespeca, Vittorio, Quax, Rick, Rikkert, Marcel G. M. Olde, Korzilius, Hubert P. L. M., Marchau, Vincent A. W. J., Hadijsotiriou, Sophie, Oreel, Tom, Coenen, Jannie, Wertheim, Heiman, Voinov, Alexey, Rouwette, Etiënne A. J. A., Vasconcelos, Vítor V.
Policymaking for complex challenges such as pandemics necessitates the consideration of intricate implications across multiple domains and scales. Computational models can support policymaking, but a single model is often insufficient for such multid
Externí odkaz:
http://arxiv.org/abs/2402.06228
We examine the relationship of graded (multi)modal logic to counting (multichannel) message passing automata with applications to the Weisfeiler-Leman algorithm. We introduce the notion of graded multimodal types, which are formulae of graded multimo
Externí odkaz:
http://arxiv.org/abs/2401.06519
Autor:
Ou, Yunbo, Mirzhalilov, Murod, Nemes, Norbert M., Martinez, Jose L., Rocci, Mirko, Duong, Alexander, Akey, Austin, Ge, Wenbo, Suri, Dhavala, Wang, Yiping, Ambaye, Haile, Keum, Jong, Randeria, Mohit, Trivedi, Nandini, Burch, Kenneth S., Bell, David C., Wu, Weida, Heiman, Don, Lauter, Valeria, Moodera, Jagadeesh S., Chi, Hang
Exchange-coupled interfaces are pivotal in exploiting two-dimensional (2D) ferromagnetism. Due to the extraordinary correlations among charge, spin, orbital and lattice degrees of freedom, layered magnetic transition metal chalcogenides (TMCs) bode w
Externí odkaz:
http://arxiv.org/abs/2312.15028
Autor:
Vilela, G. L. S., Stephen, G. M., Gratens, X., Galgano, G. D., Hou, Yasen, Takamura, Y., Heiman, D., Henriques, A., Berera, G., Moodera, J. S.
Rare-earth nitrides, such as gadolinium nitride (GdN), have great potential for spintronic devices due to their unique magnetic and electronic properties. GdN has a large magnetic moment, low coercitivity and strong spin polarization suitable for spi
Externí odkaz:
http://arxiv.org/abs/2309.06666
We investigate the descriptive complexity of a class of neural networks with unrestricted topologies and piecewise polynomial activation functions. We consider the general scenario where the running time is unlimited and floating-point numbers are us
Externí odkaz:
http://arxiv.org/abs/2308.06277
Autor:
DeMell, Jennifer E., Naumov, Ivan, Stephen, Gregory M., Blumenschein, Nicholas A., Sun, Y. -J. Leo, Fedorko, Adrian, Robinson, Jeremy T., Campbell, Paul M., Taylor, Patrick J., Heiman, Don, Dev, Pratibha, Hanbicki, Aubrey T., Friedman, Adam L.
Publikováno v:
Adv. Funct. Mat., 2311875 (2023)
Mechanical stacking of two dissimilar materials often has surprising consequences for heterostructure behavior. In particular, a two-dimensional electron gas (2DEG) is formed in the heterostructure of the topological crystalline insulator Pb0.24Sn0.7
Externí odkaz:
http://arxiv.org/abs/2307.13113
Autor:
Ekgren, Ariel, Gyllensten, Amaru Cuba, Stollenwerk, Felix, Öhman, Joey, Isbister, Tim, Gogoulou, Evangelia, Carlsson, Fredrik, Heiman, Alice, Casademont, Judit, Sahlgren, Magnus
This paper details the process of developing the first native large generative language model for the Nordic languages, GPT-SW3. We cover all parts of the development process, from data collection and processing, training configuration and instructio
Externí odkaz:
http://arxiv.org/abs/2305.12987