Zobrazeno 1 - 10
of 573 527
pro vyhledávání: '"Zou, A"'
Autor:
Gao, Anning, Prochaska, Jason X., Cai, Zheng, Zou, Siwei, Zhao, Cheng, Sun, Zechang, Ahlen, S., Bianchi, D., Brooks, D., Claybaugh, T., de la Macorra, A., Dey, Arjun, Doel, P., Forero-Romero, J. E., Gaztañaga, E., Gontcho, S. Gontcho A, Gutierrez, G., Honscheid, K., Juneau, S., Kremin, A., Martini, P., Meisner, A., Miquel, R., Moustakas, J., Muñoz-Gutiérrez, A., Newman, J. A., Pérez-Ràfols, I., Rossi, G., Sanchez, E., Schubnell, M., Sprayberry, D., Tarlé, G., Weaver, B. A., Zou, H.
The mean free path of ionizing photons for neutral hydrogen ($\lambda_\mathrm{mfp}^{912}$) is a crucial quantity in modelling the ionization state of the intergalactic medium (IGM) and the extragalactic ultraviolet background (EUVB), and is widely us
Externí odkaz:
http://arxiv.org/abs/2411.15838
Autor:
Zhang, Yan-Lei, Li, Ming, Xu, Xin-Biao, Dong, Chun-Hua, Guo, Guang-Can, Xiang, Ze-Liang, Zou, Chang-Ling, Zou, and Xu-Bo
Quantum frequency converters that enable the interface between the itinerant photons and qubits are indispensable for realizing long-distance quantum network. However, the cascaded connection between converters and qubits usually brings additional in
Externí odkaz:
http://arxiv.org/abs/2411.13158
Efficient microwave-to-optical frequency conversion (MOC) is crucial for applications such as radiometry, electrometry, quantum microwave illumination and quantum networks. Rydberg atoms provide a unique platform for realizing free-space MOC, promisi
Externí odkaz:
http://arxiv.org/abs/2411.13160
Autor:
Chen, Zeyu, Wang, Enci, Zou, Hu, Zou, Siwei, Gao, Yang, Wang, Huiyuan, Yu, Haoran, Jia, Cheng, Li, Haixin, Ma, Chengyu, Yao, Yao, Ding, Weiyu, Zhu, Runyu
Understanding the circumgalactic medium (CGM) distribution of galaxies is the key to revealing the dynamical exchange of materials between galaxies and their surroundings. In this work, we use DESI EDR dataset to investigate the cool CGM of galaxies
Externí odkaz:
http://arxiv.org/abs/2411.08485
Autor:
Zhang, Yan-Lei, Jie, Qing-Xuan, Li, Ming, Wu, Shu-Hao, Wang, Zhu-Bo, Zou, Xu-Bo, Zhang, Peng-Fei, Li, Gang, Zhang, Tiancai, Guo, Guang-Can, Zou, Chang-Ling
Realizing large-scale quantum networks requires the generation of high-fidelity quantum entanglement states between remote quantum nodes, a key resource for quantum communication, distributed computation and sensing applications. However, entanglemen
Externí odkaz:
http://arxiv.org/abs/2410.12523
Autor:
Li, Jiawei, Yu, Hongwei, Chen, Jiansheng, Ding, Xinlong, Wang, Jinlong, Liu, Jinyuan, Zou, Bochao, Ma, Huimin
Infrared and visible image fusion (IVIF) is a crucial technique for enhancing visual performance by integrating unique information from different modalities into one fused image. Exiting methods pay more attention to conducting fusion with undisturbe
Externí odkaz:
http://arxiv.org/abs/2412.09954
User interactions in recommender systems are inherently complex, often involving behaviors that go beyond simple acceptance or rejection. One particularly common behavior is hesitation, where users deliberate over recommended items, signaling uncerta
Externí odkaz:
http://arxiv.org/abs/2412.09950
Autor:
He, Yingxu, Liu, Zhuohan, Sun, Shuo, Wang, Bin, Zhang, Wenyu, Zou, Xunlong, Chen, Nancy F., Aw, Ai Ti
We introduce MERaLiON-AudioLLM (Multimodal Empathetic Reasoning and Learning in One Network), the first speech-text model tailored for Singapore's multilingual and multicultural landscape. Developed under the National Large Language Models Funding In
Externí odkaz:
http://arxiv.org/abs/2412.09818
Autor:
Feng, Chun-Mei, He, Yuanyang, Zou, Jian, Khan, Salman, Xiong, Huan, Li, Zhen, Zuo, Wangmeng, Goh, Rick Siow Mong, Liu, Yong
Publikováno v:
International Journal of Computer Vision, 2025
Existing test-time prompt tuning (TPT) methods focus on single-modality data, primarily enhancing images and using confidence ratings to filter out inaccurate images. However, while image generation models can produce visually diverse images, single-
Externí odkaz:
http://arxiv.org/abs/2412.09706
Traditional data influence estimation methods, like influence function, assume that learning algorithms are permutation-invariant with respect to training data. However, modern training paradigms, especially for foundation models using stochastic alg
Externí odkaz:
http://arxiv.org/abs/2412.09538