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Autor:
Hejabi, Parsa, Rahmati, Elnaz, Ziabari, Alireza S., Golazizian, Preni, Thomason, Jesse, Dehghani, Morteza
Large Language Models (LLMs) have shown impressive capabilities in complex tasks and interactive environments, yet their creativity remains underexplored. This paper introduces a simulation framework utilizing the game Balderdash to evaluate both the
Externí odkaz:
http://arxiv.org/abs/2411.10422
Autor:
Desai, M. I., Drake, J. F., Phan, T., Yin, Z., Swisdak, M., McComas, D. J., Bale, S. D., Rahmati, A., Larson, D., Matthaeus, W. H., Dayeh, M. A., Starkey, M. J., Raouafi, N. E., Mitchell, D. G., Cohen, C. M. S., Szalay, J. R., Giacalone, J., Hill, M. E., Christian, E. R., Schwadron, N. A., McNutt Jr., R. L., Malandraki, O., Whittlesey, P., Livi, R., Kasper, J. C.
We report observations of direct evidence of energetic protons being accelerated above ~400 keV within the reconnection exhaust of a heliospheric current sheet (HCS) crossing by NASA's Parker Solar Probe (PSP) at a distance of ~16.25 solar radii (Rs)
Externí odkaz:
http://arxiv.org/abs/2410.16539
The vulnerability of machine learning models in adversarial scenarios has garnered significant interest in the academic community over the past decade, resulting in a myriad of attacks and defenses. However, while the community appears to be overtly
Externí odkaz:
http://arxiv.org/abs/2410.12076
In this paper, we investigate some properties of symbolic powers and symbolic Rees algebras of binomial edge ideals associated with some classes of block graphs. First, it is shown that symbolic powers of binomial edge ideals of pendant cliques graph
Externí odkaz:
http://arxiv.org/abs/2409.10137
Autor:
Rahmati, Amir Hossein, Fan, Mingzhou, Zhou, Ruida, Urban, Nathan M., Yoon, Byung-Jun, Qian, Xiaoning
Instead of randomly acquiring training data points, Uncertainty-based Active Learning (UAL) operates by querying the label(s) of pivotal samples from an unlabeled pool selected based on the prediction uncertainty, thereby aiming at minimizing the lab
Externí odkaz:
http://arxiv.org/abs/2408.13690
Evolving networks are complex data structures that emerge in a wide range of systems in science and engineering. Learning expressive representations for such networks that encode their structural connectivity and temporal evolution is essential for d
Externí odkaz:
http://arxiv.org/abs/2408.12753
In computation-intensive domains such as digital signal processing, encryption, and neural networks, the performance of arithmetic units, including adders and multipliers, is pivotal. Conventional numerical systems often fall short of meeting the eff
Externí odkaz:
http://arxiv.org/abs/2408.05639
Autor:
Kachouei, Arman Ataei, Rahmati, Farhad
In this paper we extend some set theoretic concepts of numerical semigroups for arbitrary sub-semigroups of natural numbers. Then we characterized gapsets which leads to a more efficient computational approach towards numerical semigroups and finally
Externí odkaz:
http://arxiv.org/abs/2408.02425
Autor:
Rahmati, Hamidreza, Rahmati, Farhad
Blockchain is a decentralized network to increase trust, integrity, and transparency of transactions. With the exponential growth of transactions in the realm of Blockchain, especially in Bitcoin, Blockchain size increases as all transactions must be
Externí odkaz:
http://arxiv.org/abs/2404.17787