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pro vyhledávání: '"Zach, A"'
In 1975, Stein made a wide generalisation of the Ryser-Brualdi-Stein conjecture on transversals in Latin squares, conjecturing that every equi-$n$-square (an $n\times n$ array filled with $n$ symbols where each symbol appears exactly $n$ times) has a
Externí odkaz:
http://arxiv.org/abs/2412.07733
Autor:
Girão, António, Hunter, Zach
It is easy to see that every $q$-edge-colouring of the complete graph on $2^q+1$ vertices must contain a monochromatic odd cycle. A natural question raised by Erd\H{o}s and Graham in $1973$ asks for the smallest $L(q)$ such that every $q$-edge-colour
Externí odkaz:
http://arxiv.org/abs/2412.07708
The gravitational wave detectors used by the LIGO Scientific Collaboration, and the Virgo Collaboration are incredibly sensitive instruments which frequently detect non-stationary, non-Gaussian noise transients. iDQ is a statistical inference framewo
Externí odkaz:
http://arxiv.org/abs/2412.04638
Causal reasoning is often challenging with spatial data, particularly when handling high-dimensional inputs. To address this, we propose a neural network (NN) based framework integrated with an approximate Gaussian process to manage spatial interfere
Externí odkaz:
http://arxiv.org/abs/2412.04285
It is well known that there is a duality map between the superstable configurations and the critical configurations of a graph. This was extended to all M-matrices in (Guzm\`an-Klivans 2015). We show a natural way to extend this to all $(L,M)$-chip f
Externí odkaz:
http://arxiv.org/abs/2412.02679
Autor:
Suresh, Tarun, Reddy, Revanth Gangi, Xu, Yifei, Nussbaum, Zach, Mulyar, Andriy, Duderstadt, Brandon, Ji, Heng
Effective code retrieval plays a crucial role in advancing code generation, bug fixing, and software maintenance, particularly as software systems increase in complexity. While current code embedding models have demonstrated promise in retrieving cod
Externí odkaz:
http://arxiv.org/abs/2412.01007
Autor:
Parker, Julian D, Smirnov, Anton, Pons, Jordi, Carr, CJ, Zukowski, Zack, Evans, Zach, Liu, Xubo
The tokenization of speech with neural audio codec models is a vital part of modern AI pipelines for the generation or understanding of speech, alone or in a multimodal context. Traditionally such tokenization models have concentrated on low paramete
Externí odkaz:
http://arxiv.org/abs/2411.19842
More than 40 years ago, Galvin, Rival and Sands showed that every $K_{s, s}$-free graph containing an $n$-vertex path must contain an induced path of length $f(n)$, where $f(n)\to \infty$ as $n\to \infty$. Recently, it was shown by Duron, Esperet and
Externí odkaz:
http://arxiv.org/abs/2411.19173
Autor:
Bercovich, Akhiad, Ronen, Tomer, Abramovich, Talor, Ailon, Nir, Assaf, Nave, Dabbah, Mohammad, Galil, Ido, Geifman, Amnon, Geifman, Yonatan, Golan, Izhak, Haber, Netanel, Karpas, Ehud, Koren, Roi, Levy, Itay, Molchanov, Pavlo, Mor, Shahar, Moshe, Zach, Nabwani, Najeeb, Puny, Omri, Rubin, Ran, Schen, Itamar, Shahaf, Ido, Tropp, Oren, Argov, Omer Ullman, Zilberstein, Ran, El-Yaniv, Ran
Large language models (LLMs) have demonstrated remarkable capabilities, but their adoption is limited by high computational costs during inference. While increasing parameter counts enhances accuracy, it also widens the gap between state-of-the-art c
Externí odkaz:
http://arxiv.org/abs/2411.19146
Predicting crash likelihood in complex driving environments is essential for improving traffic safety and advancing autonomous driving. Previous studies have used statistical models and deep learning to predict crashes based on semantic, contextual,
Externí odkaz:
http://arxiv.org/abs/2411.17886