Zobrazeno 1 - 10
of 11 296
pro vyhledávání: '"Bertsch, A."'
We review the relationship between discrete groups of symmetries of Euclidean three-space, constructions in algebraic geometry around Kleinian singularities including versions of Hilbert and Quot schemes, and their relationship to finite-dimensional
Externí odkaz:
http://arxiv.org/abs/2410.17860
General-purpose LLM judges capable of human-level evaluation provide not only a scalable and accurate way of evaluating instruction-following LLMs but also new avenues for supervising and improving their performance. One promising way of leveraging L
Externí odkaz:
http://arxiv.org/abs/2410.02902
Autor:
Miller, Daniel, Levi, Kyano, Postler, Lukas, Steiner, Alex, Bittel, Lennart, White, Gregory A. L., Tang, Yifan, Kuehnke, Eric J., Mele, Antonio A., Khatri, Sumeet, Leone, Lorenzo, Carrasco, Jose, Marciniak, Christian D., Pogorelov, Ivan, Guevara-Bertsch, Milena, Freund, Robert, Blatt, Rainer, Schindler, Philipp, Monz, Thomas, Ringbauer, Martin, Eisert, Jens
Throughout its history, the theory of quantum error correction has heavily benefited from translating classical concepts into the quantum setting. In particular, classical notions of weight enumerators, which relate to the performance of an error-cor
Externí odkaz:
http://arxiv.org/abs/2408.16914
Autor:
Hagino, K., Bertsch, G. F.
Nuclear fission at barrier-top energies is conventionally modeled by a one-dimensional Schr\"odinger equation applied to internal fission channels, but that treatment is hard to justify in the configuration-interaction approach to nuclear Hamiltonian
Externí odkaz:
http://arxiv.org/abs/2408.11427
Large language models pretrained on extensive web corpora demonstrate remarkable performance across a wide range of downstream tasks. However, a growing concern is data contamination, where evaluation datasets may be contained in the pretraining corp
Externí odkaz:
http://arxiv.org/abs/2407.08716
Autor:
Welleck, Sean, Bertsch, Amanda, Finlayson, Matthew, Schoelkopf, Hailey, Xie, Alex, Neubig, Graham, Kulikov, Ilia, Harchaoui, Zaid
One of the most striking findings in modern research on large language models (LLMs) is that scaling up compute during training leads to better results. However, less attention has been given to the benefits of scaling compute during inference. This
Externí odkaz:
http://arxiv.org/abs/2406.16838
The oscillating magnetic field produced by unbalanced currents in radio-frequency ion traps induces transition frequency shifts and sideband transitions that can be harmful to precision spectroscopy experiments. Here, we describe a methodology, based
Externí odkaz:
http://arxiv.org/abs/2405.18883
Autor:
Devine, M. T., Bertsch, V.
To meet carbon emission targets, governments around the world seek electricity consumers to invest in self-sufficiency technologies such as solar photovoltaic and battery storage. Such behaviour is sought in markets typically characterised by an olig
Externí odkaz:
http://arxiv.org/abs/2405.17223
Autor:
Bertsch, Amanda, Ivgi, Maor, Alon, Uri, Berant, Jonathan, Gormley, Matthew R., Neubig, Graham
As model context lengths continue to increase, the number of demonstrations that can be provided in-context approaches the size of entire training datasets. We study the behavior of in-context learning (ICL) at this extreme scale on multiple datasets
Externí odkaz:
http://arxiv.org/abs/2405.00200
Publikováno v:
EPJ Web of Conferences 306, 01027 (2024)
Even though more than 80 years have passed since the discovery of fission, its microscopic understanding has still been unclear. To clarify the underlying mechanics of induced fission, we analyze the distribution of a fission width using a miscropic
Externí odkaz:
http://arxiv.org/abs/2404.05500