Zobrazeno 1 - 10
of 74 590
pro vyhledávání: '"At, Vo"'
Publikováno v:
IEEE Transactions on Signal Processing, vol. 72, 2024, pp. 4888-4917
This article presents the Labeled Random Finite Set (LRFS) framework for multi-object systems-systems in which the number of objects and their states are unknown and vary randomly with time. In particular, we focus on state and trajectory estimation
Externí odkaz:
http://arxiv.org/abs/2409.18531
Autor:
Chaiyachad, Sujinda, Vo, Trung-Phuc, Singsen, Sirisak, Eknapakul, Tanachat, Jindata, Warakorn, Jaisuk, Chutchawan, Fevre, Patrick Le, Bertran, Francois, Lu, Donghui, Huang, Yaobo, Nakajima, Hideki, Liewrian, Watchara, Fongkaew, Ittipon, Minar, Jan, Meevasana, Worawat
Graphite, conventionally regarded as a gapless material, exhibits a bandgap of ~100 meV in nano-scale patterned highly oriented pyrolytic graphite (HOPG), as revealed by angle-resolved photoemission spectroscopy (ARPES). Our advanced first-principles
Externí odkaz:
http://arxiv.org/abs/2411.14244
Autor:
Nguyen, Christopher, Nguyen, William, Suzuki, Atsushi, Oku, Daisuke, Phan, Hong An, Dinh, Sang, Nguyen, Zooey, Ha, Anh, Raghavan, Shruti, Vo, Huy, Nguyen, Thang, Nguyen, Lan, Hirayama, Yoshikuni
Large Language Models (LLMs) have demonstrated the potential to address some issues within the semiconductor industry. However, they are often general-purpose models that lack the specialized knowledge needed to tackle the unique challenges of this s
Externí odkaz:
http://arxiv.org/abs/2411.13802
Autor:
Nguyen, Quang Vinh, Son, Vo Hoang Thanh, Hoang, Chau Truong Vinh, Nguyen, Duc Duy, Minh, Nhat Huy Nguyen, Kim, Soo-Hyung
Naturalistic driving action localization task aims to recognize and comprehend human behaviors and actions from video data captured during real-world driving scenarios. Previous studies have shown great action localization performance by applying a r
Externí odkaz:
http://arxiv.org/abs/2411.12525
In this paper, we propose ZeFaV - a zero-shot based fact-checking verification framework to enhance the performance on fact verification task of large language models by leveraging the in-context learning ability of large language models to extract t
Externí odkaz:
http://arxiv.org/abs/2411.11247
Layered Multiple Scattering Approach to Hard X-ray Photoelectron Diffraction: Theory and Application
Autor:
Vo, Trung-Phuc, Tkach, Olena, Tricot, Sylvain, Sebilleau, Didier, Braun, Jurgen, Pulkkinen, Aki, Winkelmann, Aimo, Fedchenko, Olena, Lytvynenko, Yaryna, Vasilyev, Dmitry, Elmers, Hans-Joachim, Schonhense, Gerd, Minar, Jan
Photoelectron diffraction (PED) is a powerful and essential experimental technique for resolving the structure of surfaces with sub-angstrom resolution. In the high energy regime, researchers in angle-resolved photoemission spectroscopy (ARPES) obser
Externí odkaz:
http://arxiv.org/abs/2411.09669
Autor:
Leto, Alexandria, Aguerrebere, Cecilia, Bhati, Ishwar, Willke, Ted, Tepper, Mariano, Vo, Vy Ai
Retrieval-augmented generation (RAG) is a promising method for addressing some of the memory-related challenges associated with Large Language Models (LLMs). Two separate systems form the RAG pipeline, the retriever and the reader, and the impact of
Externí odkaz:
http://arxiv.org/abs/2411.07396
Polariton lasing is a promising phenomenon with potential applications in next-generation lasers that operate without the need for population inversion. Applying a perpendicular magnetic field to a quantum well (QW) significantly alters the propertie
Externí odkaz:
http://arxiv.org/abs/2411.02458
We extend the Wirtinger number of links, an invariant originally defined by Blair et al. in terms of extending initial colorings of some strands of a diagram to the entire diagram, to spatial graphs. We prove that the Wirtinger number equals the brid
Externí odkaz:
http://arxiv.org/abs/2410.23253
Autor:
Manh, Cuong Tran, Vo, Hieu Dinh
While smart contracts are foundational elements of blockchain applications, their inherent susceptibility to security vulnerabilities poses a significant challenge. Existing training datasets employed for vulnerability detection tools may be limited,
Externí odkaz:
http://arxiv.org/abs/2410.21685