Zobrazeno 1 - 10
of 31 713
pro vyhledávání: '"P. Silvio"'
Fisher information is a fundamental concept in various physical and metrological theories. By defining an analogous stochastic quantity called Stochastic Fisher Information (SFI), we uncover two fluctuation relations with an inherent geometric nature
Externí odkaz:
http://arxiv.org/abs/2410.23939
Autor:
Ginart, Antonio A., Kodali, Naveen, Lee, Jason, Xiong, Caiming, Savarese, Silvio, Emmons, John
While frontier large language models (LLMs) are capable tool-using agents, current AI systems still operate in a strict turn-based fashion, oblivious to passage of time. This synchronous design forces user queries and tool-use to occur sequentially,
Externí odkaz:
http://arxiv.org/abs/2410.21620
Autor:
Liu, Zhiwei, Yao, Weiran, Zhang, Jianguo, Murthy, Rithesh, Yang, Liangwei, Liu, Zuxin, Lan, Tian, Zhu, Ming, Tan, Juntao, Kokane, Shirley, Hoang, Thai, Niebles, Juan Carlos, Heinecke, Shelby, Wang, Huan, Savarese, Silvio, Xiong, Caiming
We introduce the Principled Reasoning and Acting (PRAct) framework, a novel method for learning and enforcing action principles from trajectory data. Central to our approach is the use of text gradients from a reflection and optimization engine to de
Externí odkaz:
http://arxiv.org/abs/2410.18528
The truncated Floquet-Bloch transform can be used to characterise the spectral properties of finite periodic and aperiodic large systems of resonators. This paper aims to provide for the first time the mathematical foundations of this transform.
Externí odkaz:
http://arxiv.org/abs/2410.17597
Autor:
Ryoo, Michael S., Zhou, Honglu, Kendre, Shrikant, Qin, Can, Xue, Le, Shu, Manli, Savarese, Silvio, Xu, Ran, Xiong, Caiming, Niebles, Juan Carlos
We present xGen-MM-Vid (BLIP-3-Video): a multimodal language model for videos, particularly designed to efficiently capture temporal information over multiple frames. BLIP-3-Video takes advantage of the 'temporal encoder' in addition to the conventio
Externí odkaz:
http://arxiv.org/abs/2410.16267
Autor:
Sorrentino, Ines, Romualdi, Giulio, Bergonti, Fabio, ĽErario, Giuseppe, Traversaro, Silvio, Pucci, Daniele
This paper presents a scalable method for friction identification in robots equipped with electric motors and high-ratio harmonic drives, utilizing Physics-Informed Neural Networks (PINN). This approach eliminates the need for dedicated setups and jo
Externí odkaz:
http://arxiv.org/abs/2410.12685
In this paper, we consider the \emph{metric $k$-center} problem in the fully dynamic setting, where we are given a metric space $(V,d)$ evolving via a sequence of point insertions and deletions and our task is to maintain a subset $S \subseteq V$ of
Externí odkaz:
http://arxiv.org/abs/2410.11470
Autor:
Bauhofer, Maximilian, Henninger, Marcus, Wild, Thorsten, Brink, Stephan ten, Mandelli, Silvio
The distributed nature of cellular networks is one of the main enablers for integrated sensing and communication (ISAC). For target positioning and tracking, making use of bistatic measurements is non-trivial due to their non-linear relationship with
Externí odkaz:
http://arxiv.org/abs/2410.11681
Autor:
Liu, Xu, Liu, Juncheng, Woo, Gerald, Aksu, Taha, Liang, Yuxuan, Zimmermann, Roger, Liu, Chenghao, Savarese, Silvio, Xiong, Caiming, Sahoo, Doyen
Time series foundation models have demonstrated impressive performance as zero-shot forecasters. However, achieving effectively unified training on time series remains an open challenge. Existing approaches introduce some level of model specializatio
Externí odkaz:
http://arxiv.org/abs/2410.10469
Autor:
Aksu, Taha, Woo, Gerald, Liu, Juncheng, Liu, Xu, Liu, Chenghao, Savarese, Silvio, Xiong, Caiming, Sahoo, Doyen
Time series foundation models excel in zero-shot forecasting, handling diverse tasks without explicit training. However, the advancement of these models has been hindered by the lack of comprehensive benchmarks. To address this gap, we introduce the
Externí odkaz:
http://arxiv.org/abs/2410.10393