Zobrazeno 1 - 10
of 13 579
pro vyhledávání: '"Soh P"'
Current social navigation methods and benchmarks primarily focus on proxemics and task efficiency. While these factors are important, qualitative aspects such as perceptions of a robot's social competence are equally crucial for successful adoption a
Externí odkaz:
http://arxiv.org/abs/2412.19595
Autor:
Ke, Yu He, Jin, Liyuan, Elangovan, Kabilan, Ong, Bryan Wen Xi, Oh, Chin Yang, Sim, Jacqueline, Loh, Kenny Wei-Tsen, Soh, Chai Rick, Cheng, Jonathan Ming Hua, Lee, Aaron Kwang Yang, Ting, Daniel Shu Wei, Liu, Nan, Abdullah, Hairil Rizal
Large Language Models (LLMs) are emerging as powerful tools in healthcare, particularly for complex, domain-specific tasks. This study describes the development and evaluation of the PErioperative AI CHatbot (PEACH), a secure LLM-based system integra
Externí odkaz:
http://arxiv.org/abs/2412.18096
Dealing with missing data poses significant challenges in predictive analysis, often leading to biased conclusions when oversimplified assumptions about the missing data process are made. In cases where the data are missing not at random (MNAR), join
Externí odkaz:
http://arxiv.org/abs/2412.14946
Autor:
Uematsu, Ryosuke, Ueda, Yoshihiro, Alexander, David M., Swinbank, A. M., Smail, Ian, Andonie, Carolina, Chen, Chian-Chou, Dudzeviciute, Ugne, Ikarashi, Soh, Kohno, Kotaro, Matsuda, Yuichi, Puglisi, Annagrazia, Umehata, Hideki, Wang, Wei-Hao
We investigate the properties of active galactic nuclei (AGNs) in the brightest submillimeter galaxies (SMGs) in the COSMOS field. We utilize the bright sample of ALMA/SCUBA-2 COSMOS Survey (AS2COSMOS), which consists of 260 SMGs with $S_{\mathrm{870
Externí odkaz:
http://arxiv.org/abs/2412.09737
Quantum Reservoir Computing (QRC) leverages quantum systems to perform complex computational tasks with exceptional efficiency and reduced energy consumption. We introduce a minimalistic QRC framework utilizing only a few two-level atoms in a single-
Externí odkaz:
http://arxiv.org/abs/2412.17817
Graphical structure learning is an effective way to assess and visualize cross-biomarker dependencies in biomedical settings. Standard approaches to estimating graphs rely on conditional independence tests that may not be sensitive to associations th
Externí odkaz:
http://arxiv.org/abs/2411.17033
Trusted Execution Environments (TEEs) are critical components of modern secure computing, providing isolated zones in processors to safeguard sensitive data and execute secure operations. Despite their importance, TEEs are increasingly vulnerable to
Externí odkaz:
http://arxiv.org/abs/2411.14878
Autor:
Do, Hue T. B., Zhao, Meng, Li, Pengfei, Soh, Yu Wei, Rangaraj, Jagadesh, Liu, Bingyan, Jiang, Tianyu, Zhang, Xinyue, Lu, Jiong, Song, Peng, Teng, Jinghua, Bosman, Michel
Extreme light confinement down to the atomic scale has been theoretically predicted for ultrathin, Ta-based transition metal dichalcogenides (TMDs). In this work, we demonstrate in free-hanging 2H-TaS2 monolayers and bilayers slow light behaviour wit
Externí odkaz:
http://arxiv.org/abs/2411.07572
Autor:
Kumabe, Soh
Let $\mathcal{D}$ be a set family that is the solution domain of some combinatorial problem. The \emph{max-min diversification problem on $\mathcal{D}$} is the problem to select $k$ sets from $\mathcal{D}$ such that the Hamming distance between any t
Externí odkaz:
http://arxiv.org/abs/2411.02845
This paper introduces the first generalization and adaptation benchmark using machine learning for evaluating out-of-distribution performance of electromyography (EMG) classification algorithms. The ability of an EMG classifier to handle inputs drawn
Externí odkaz:
http://arxiv.org/abs/2410.23625