Zobrazeno 1 - 10
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pro vyhledávání: '"Lee, P A"'
Autor:
Cho, Woojin, Lee, Jihyun, Yi, Minjae, Kim, Minje, Woo, Taeyun, Kim, Donghwan, Ha, Taewook, Lee, Hyokeun, Ryu, Je-Hwan, Woo, Woontack, Kim, Tae-Kyun
Existing datasets for 3D hand-object interaction are limited either in the data cardinality, data variations in interaction scenarios, or the quality of annotations. In this work, we present a comprehensive new training dataset for hand-object intera
Externí odkaz:
http://arxiv.org/abs/2409.04033
This paper offers a thorough analysis of the coverage performance of Low Earth Orbit (LEO) satellite networks using a strongest satellite association approach, with a particular emphasis on shadowing effects modeled through a Poisson point process (P
Externí odkaz:
http://arxiv.org/abs/2409.04002
Autor:
Lee, Kimyeong, Lee, Norton
We perform folding on the ADHM construction of the instanton moduli space from $SU$ to $SO$ group. A Young diagram description for the $SO$ instanton is obtained after modifying the real and complex moment maps of the ADHM data. We study the Bethe ga
Externí odkaz:
http://arxiv.org/abs/2409.03483
Autor:
Lee, Jun-Young, Kim, Ji-hoon, Jung, Minyong, Oh, Boon Kiat, Jo, Yongseok, Park, Songyoun, Lee, Jaehyun, Ting, Yuan-Sen, Hwang, Ho Seong
We present a proof-of-concept simulation-based inference on $\Omega_{\rm m}$ and $\sigma_{8}$ from the SDSS BOSS LOWZ NGC catalog using neural networks and domain generalization techniques without the need of summary statistics. Using rapid lightcone
Externí odkaz:
http://arxiv.org/abs/2409.02256
This study introduces a comprehensive benchmark designed to evaluate the performance of large language models (LLMs) in understanding and processing cultural knowledge, with a specific focus on Hakka culture as a case study. Leveraging Bloom's Taxono
Externí odkaz:
http://arxiv.org/abs/2409.01556
Autor:
Marzec, E., Ajimura, S., Antonakis, A., Botran, M., Cheoun, M. K., Choi, J. H., Choi, J. W., Choi, J. Y., Dodo, T., Furuta, H., Goh, J. H., Haga, K., Harada, M., Hasegawa, S., Hino, Y., Hiraiwa, T., Hwang, W., Iida, T., Iwai, E., Iwata, S., Jang, H. I., Jang, J. S., Jang, M. C., Jeon, H. K., Jeon, S. H., Joo, K. K., Jung, D. E., Kang, S. K., Kasugai, Y., Kawasaki, T., Kim, E. J., Kim, J. Y., Kim, E. M., Kim, S. Y., Kim, W., Kim, S. B., Kinoshita, H., Konno, T., Kuwata, K., Lee, D. H., Lee, S., Lim, I. T., Little, C., Maruyama, T., Masuda, S., Meigo, S., Monjushiro, S., Moon, D. H., Nakano, T., Niiyama, M., Nishikawa, K., Noumachi, M., Pac, M. Y., Park, B. J., Park, H. W., Park, J. B., Park, J. S., Park, R. G., Peeters, S. J. M., Roellinghoff, G., Rott, C., Ryu, J. W., Sakai, K., Sakamoto, S., Shima, T., Shin, C. D., Spitz, J., Stancu, I., Suekane, F., Sugaya, Y., Suzuya, K., Taira, M., Takeuchi, Y., Wang, W., Waterfield, J., Wei, W., White, R., Yamaguchi, Y., Yeh, M., Yeo, I. S., Yoo, C., Yu, I., Zohaib, A.
We present the first measurement of the missing energy due to nuclear effects in monoenergetic, muon neutrino charged-current interactions on carbon, originating from $K^+ \rightarrow \mu^+ \nu_\mu$ decay-at-rest ($E_{\nu_\mu}=235.5$ MeV), performed
Externí odkaz:
http://arxiv.org/abs/2409.01383
Sequential recommendation aims to predict the next item a user is likely to prefer based on their sequential interaction history. Recently, text-based sequential recommendation has emerged as a promising paradigm that uses pre-trained language models
Externí odkaz:
http://arxiv.org/abs/2409.00702
Autor:
Lee, Jihyun, Lee, Kyungyong
Let $Q$ be a rank 3 mutation-cyclic quiver. It is known that every $\mathbf{c}$-vector of $Q$ is a solution to a quadratic equation of the form $$\sum_{i=1}^3 x_i^2 + \sum_{1\leq i
Externí odkaz:
http://arxiv.org/abs/2409.00599
Autor:
Yang, Dongil, Lee, Suyeon, Kim, Minjin, Won, Jungsoo, Kim, Namyoung, Lee, Dongha, Yeo, Jinyoung
Engagement between instructors and students plays a crucial role in enhancing students'academic performance. However, instructors often struggle to provide timely and personalized support in large classes. To address this challenge, we propose a nove
Externí odkaz:
http://arxiv.org/abs/2409.00355
Autor:
Lee, Unggi, Bae, Jiyeong, Jung, Yeonji, Kang, Minji, Byun, Gyuri, Lee, Yeonseo, Kim, Dohee, Lee, Sookbun, Park, Jaekwon, Ahn, Taekyung, Lee, Gunho, Kim, Hyeoncheol
Knowledge Tracing (KT) is a critical component in online learning, but traditional approaches face limitations in interpretability and cross-domain adaptability. This paper introduces Language Model-based Code Knowledge Tracing (CodeLKT), an innovati
Externí odkaz:
http://arxiv.org/abs/2409.00323