Zobrazeno 1 - 10
of 24 435
pro vyhledávání: '"A. Tomer"'
A tournament is an orientation of a complete graph. A vertex that can reach every other vertex within two steps is called a \emph{king}. We study the complexity of finding $k$ kings in a tournament graph. We show that the randomized query complexity
Externí odkaz:
http://arxiv.org/abs/2410.10475
Editing real images using a pre-trained text-to-image (T2I) diffusion/flow model often involves inverting the image into its corresponding noise map. However, inversion by itself is typically insufficient for obtaining satisfactory results, and there
Externí odkaz:
http://arxiv.org/abs/2412.08629
Autor:
Goldfriend, Tomer, Reichental, Israel, Naveh, Amir, Gazit, Lior, Yoran, Nadav, Alon, Ravid, Ur, Shmuel, Lahav, Shahak, Cornfeld, Eyal, Elazari, Avi, Emanuel, Peleg, Harpaz, Dor, Michaeli, Tal, Erez, Nati, Preminger, Lior, Shapira, Roman, Garcell, Erik Michael, Samimi, Or, Kisch, Sara, Hallel, Gil, Kishony, Gilad, van Wingerden, Vincent, Rosenbloom, Nathaniel A., Opher, Ori, Vax, Matan, Smoler, Ariel, Danzig, Tamuz, Schirman, Eden, Sella, Guy, Cohen, Ron, Garfunkel, Roi, Cohn, Tali, Rosemarin, Hanan, Hass, Ron, Jankiewicz, Klem, Gharra, Karam, Roth, Ori, Azar, Barak, Asban, Shahaf, Linkov, Natalia, Segman, Dror, Sahar, Ohad, Davidson, Niv, Minerbi, Nir, Naveh, Yehuda
We present a scalable, robust approach to creating quantum programs of arbitrary size and complexity. The approach is based on the true abstraction of the problem. The quantum program is expressed in terms of a high-level model together with constrai
Externí odkaz:
http://arxiv.org/abs/2412.07372
Estimating uncertainty in Large Language Models (LLMs) is important for properly evaluating LLMs, and ensuring safety for users. However, prior approaches to uncertainty estimation focus on the final answer in generated text, ignoring intermediate st
Externí odkaz:
http://arxiv.org/abs/2412.07961
Cooperation is vital to our survival and progress. Evolutionary game theory offers a lens to understand the structures and incentives that enable cooperation to be a successful strategy. As artificial intelligence agents become integral to human syst
Externí odkaz:
http://arxiv.org/abs/2412.06855
Autor:
Schliserman, Matan, Koren, Tomer
We study the problem of learning vector-valued linear predictors: these are prediction rules parameterized by a matrix that maps an $m$-dimensional feature vector to a $k$-dimensional target. We focus on the fundamental case with a convex and Lipschi
Externí odkaz:
http://arxiv.org/abs/2412.04274
Autor:
Eini, Tomer, Quintela, M. F. C. Martins, Henriques, J. C. G., Ribeiro, R. M., Mazor, Yarden, Peres, N. M. R., Epstein, Itai
Collective excitations of charged particles in response to electromagnetic fields give rise to a rich variety of hybrid light-matter quasiparticles with unique properties. In metals, intraband collective response characterized by negative permittivit
Externí odkaz:
http://arxiv.org/abs/2412.03139
Autor:
Shalev-Shwartz, Shai, Shashua, Amnon, Beniamini, Gal, Levine, Yoav, Sharir, Or, Wies, Noam, Ben-Shaul, Ido, Nussbaum, Tomer, Peled, Shir Granot
Artificial Expert Intelligence (AEI) seeks to transcend the limitations of both Artificial General Intelligence (AGI) and narrow AI by integrating domain-specific expertise with critical, precise reasoning capabilities akin to those of top human expe
Externí odkaz:
http://arxiv.org/abs/2412.02441
We present ReHub, a novel graph transformer architecture that achieves linear complexity through an efficient reassignment technique between nodes and virtual nodes. Graph transformers have become increasingly important in graph learning for their ab
Externí odkaz:
http://arxiv.org/abs/2412.01519
Autor:
Ravid, Tomer
I review the formalism of patch bosonization of Fermi surfaces, with a focus on the problem of a two-dimensional metal at a quantum critical point. I argue that this formalism is fundamentally inapplicable to the problem, except in synthetic limits.
Externí odkaz:
http://arxiv.org/abs/2412.00924