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Pointing Accuracy Improvements for the South Pole Telescope with Machine Learning

Autor: Chichura, P. M., Rahlin, A., Anderson, A. J., Ansarinejad, B., Archipley, M., Balkenhol, L., Benabed, K., Bender, A. N., Benson, B. A., Bianchini, F., Bleem, L. E., Bouchet, F. R., Bryant, L., Camphuis, E., Carlstrom, J. E., Chang, C. L., Chaubal, P., Chokshi, A., Chou, T. -L., Coerver, A., Crawford, T. M., Daley, C., de Haan, T., Dibert, K. R., Dobbs, M. A., Doohan, M., Doussot, A., Dutcher, D., Everett, W., Feng, C., Ferguson, K. R., Fichman, K., Foster, A., Galli, S., Gambrel, A. E., Gardner, R. W., Ge, F., Goeckner-Wald, N., Gualtieri, R., Guidi, F., Guns, S., Halverson, N. W., Hivon, E., Holder, G. P., Holzapfel, W. L., Hood, J. C., Hryciuk, A., Huang, N., Kéruzoré, F., Khalife, A. R., Kim, J., Knox, L., Korman, M., Kornoelje, K., Kuo, C. -L., Levy, K., Lowitz, A. E., Lu, C., Maniyar, A., Marrone, D. P., Martsen, E. S., Menanteau, F., Millea, M., Montgomery, J., Nakato, Y., Natoli, T., Noble, G. I., Omori, Y., Padin, S., Pan, Z., Paschos, P., Phadke, K. A., Pollak, A. W., Prabhu, K., Quan, W., Rahimi, M., Reichardt, C. L., Rouble, M., Ruhl, J. E., Schiappucci, E., Sobrin, J. A., Stark, A. A., Stephen, J., Tandoi, C., Thorne, B., Trendafilova, C., Umilta, C., Veitch-Michaelis, J., Vieira, J. D., Vitrier, A., Wan, Y., Whitehorn, N., Wu, W. L. K., Young, M. R., Zagorski, K., Zebrowski, J. A.

We present improvements to the pointing accuracy of the South Pole Telescope (SPT) using machine learning. The ability of the SPT to point accurately at the sky is limited by its structural imperfections, which are impacted by the extreme weather at

Externí odkaz: http://arxiv.org/abs/2412.15167

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The One RING: a Robotic Indoor Navigation Generalist

Autor: Eftekhar, Ainaz, Weihs, Luca, Hendrix, Rose, Caglar, Ege, Salvador, Jordi, Herrasti, Alvaro, Han, Winson, VanderBil, Eli, Kembhavi, Aniruddha, Farhadi, Ali, Krishna, Ranjay, Ehsani, Kiana, Zeng, Kuo-Hao

Modern robots vary significantly in shape, size, and sensor configurations used to perceive and interact with their environments. However, most navigation policies are embodiment-specific; a policy learned using one robot's configuration does not typ

Externí odkaz: http://arxiv.org/abs/2412.14401

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CRM: Retrieval Model with Controllable Condition

Autor: Liu, Chi, Cao, Jiangxia, Huang, Rui, Cai, Kuo, Ding, Weifeng, Luo, Qiang, Gai, Kun, Zhou, Guorui

Recommendation systems (RecSys) are designed to connect users with relevant items from a vast pool of candidates while aligning with the business goals of the platform. A typical industrial RecSys is composed of two main stages, retrieval and ranking

Externí odkaz: http://arxiv.org/abs/2412.13844

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Charmful two-body $\Omega_b$ decays in the light-front quark model

Autor: Wang, Yan-Li, Hsiao, Yu-Kuo, Wang, Kai-Lei, Lih, Chong-Chung

We investigate the singly and doubly charmful two-body $\Omega_b^-$ decays using the light-front quark model. Our findings reveal that most branching fractions calculated in this study, such as ${\cal B}(\Omega_b^-\to\Xi^- D^0,\Xi^{-}D^{*0}) = (1.0^{

Externí odkaz: http://arxiv.org/abs/2412.11584

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Probabilistic GOSPA: A Metric for Performance Evaluation of Multi-Object Filters with Uncertainties

Autor: Xia, Yuxuan, García-Fernández, Ángel F., Karlsson, Johan, Yuan, Ting, Chang, Kuo-Chu, Svensson, Lennart

This paper presents a probabilistic generalization of the generalized optimal subpattern assignment (GOSPA) metric, termed P-GOSPA metric. GOSPA is a popular metric for evaluating the distance between finite sets, typically in multi-object estimation

Externí odkaz: http://arxiv.org/abs/2412.11482

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V-MIND: Building Versatile Monocular Indoor 3D Detector with Diverse 2D Annotations

Autor: Jhang, Jin-Cheng, Tu, Tao, Wang, Fu-En, Zhang, Ke, Sun, Min, Kuo, Cheng-Hao

The field of indoor monocular 3D object detection is gaining significant attention, fueled by the increasing demand in VR/AR and robotic applications. However, its advancement is impeded by the limited availability and diversity of 3D training data,

Externí odkaz: http://arxiv.org/abs/2412.11412

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Deep learning assisted SERS detection of prolines and hydroxylated prolines using nitrilotriacetic acid functionalized gold nanopillars

Autor: Zhang, Yuan, Zhan, Kuo, Xin, Peilin, Zhao, Yingqi, Wang, Shubo, Hubarevich, Aliaksandr, Zhang, Xuejin, Huang, Jianan

Proline (Pro) is one kind of proteinogenic amino acid and an important signaling molecule in the process of metabolism. Hydroxyproline (Hyp) is a product on Pro oxygen sensing post-translational modification (PTM), which is efficiently modulated tumo

Externí odkaz: http://arxiv.org/abs/2412.08239

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SAT: Spatial Aptitude Training for Multimodal Language Models

Autor: Ray, Arijit, Duan, Jiafei, Tan, Reuben, Bashkirova, Dina, Hendrix, Rose, Ehsani, Kiana, Kembhavi, Aniruddha, Plummer, Bryan A., Krishna, Ranjay, Zeng, Kuo-Hao, Saenko, Kate

Spatial perception is a fundamental component of intelligence. While many studies highlight that large multimodal language models (MLMs) struggle to reason about space, they only test for static spatial reasoning, such as categorizing the relative po

Externí odkaz: http://arxiv.org/abs/2412.07755

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ReF-LDM: A Latent Diffusion Model for Reference-based Face Image Restoration

Autor: Hsiao, Chi-Wei, Liu, Yu-Lun, Yang, Cheng-Kun, Kuo, Sheng-Po, Jou, Kevin, Chen, Chia-Ping

While recent works on blind face image restoration have successfully produced impressive high-quality (HQ) images with abundant details from low-quality (LQ) input images, the generated content may not accurately reflect the real appearance of a pers

Externí odkaz: http://arxiv.org/abs/2412.05043

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