Zobrazeno 1 - 10
of 9 605
pro vyhledávání: '"Li,Ran"'
Autor:
Li, Ran
Recently, it was shown by Danielson-Satishchandran-Wald (DSW) that for the massive or charged body in a quantum spatial separated superposition state, the presence of a black hole can decohere the superposition inevitably towards capturing the radiat
Externí odkaz:
http://arxiv.org/abs/2411.04734
Autor:
Lange, Samuel C., Amvrosiadis, Aristeidis, Nightingale, James W., He, Qiuhan, Frenk, Carlos S., Robertson, Andrew, Cole, Shaun, Massey, Richard, Cao, Xiaoyue, Li, Ran, Wang, Kaihao
We analyze two galaxy-scale strong gravitational lenses, SPT0418-47 and SPT2147-50, using JWST NIRCam imaging across multiple filters. To account for angular complexity in the lens mass distribution, we introduce multipole perturbations with orders $
Externí odkaz:
http://arxiv.org/abs/2410.12987
Large language models (LLMs) have exhibited remarkable fluency across various tasks. However, their unethical applications, such as disseminating disinformation, have become a growing concern. Although recent works have proposed a number of LLM detec
Externí odkaz:
http://arxiv.org/abs/2410.03658
Autor:
Li, Xin, Chen, Weize, Chu, Qizhi, Li, Haopeng, Sun, Zhaojun, Li, Ran, Qian, Chen, Wei, Yiwei, Liu, Zhiyuan, Shi, Chuan, Sun, Maosong, Yang, Cheng
The need to analyze graphs is ubiquitous across various fields, from social networks to biological research and recommendation systems. Therefore, enabling the ability of large language models (LLMs) to process graphs is an important step toward more
Externí odkaz:
http://arxiv.org/abs/2409.19667
Autor:
Zhang, Shiliang, Fang, Guanwen, Song, Jie, Li, Ran, Gu, Yizhou, Lin, Zesen, Zhou, Chichun, Dai, Yao, Kong, Xu
Publikováno v:
Research in Astronomy and Astrophysics 24 (2024) 095012
Most existing star-galaxy classifiers depend on the reduced information from catalogs, necessitating careful data processing and feature extraction. In this study, we employ a supervised machine learning method (GoogLeNet) to automatically classify s
Externí odkaz:
http://arxiv.org/abs/2409.13296
Autor:
Feng, Hui-Mei, Cao, Zi-Huang, Lam, Man I, Li, Ran, Tian, Hao, Zhang, Xin, Wei, Peng, Li, Xin-Feng, Wang, Wei, Jones, Hugh R. A., Liu, Mao-Yuan, Liu, Chao
In this study, we conducted simulations to find the geometric aberrations expected for images taken by the Main Survey Camera (MSC) of the Chinese Space Station Telescope (CSST) due to its motion. As anticipated by previous work, our findings indicat
Externí odkaz:
http://arxiv.org/abs/2408.12929
Large language models (LLMs) can be abused at scale to create non-factual content and spread disinformation. Detecting LLM-generated content is essential to mitigate these risks, but current classifiers often fail to generalize in open-world contexts
Externí odkaz:
http://arxiv.org/abs/2408.04237
Autor:
Chen, Weize, You, Ziming, Li, Ran, Guan, Yitong, Qian, Chen, Zhao, Chenyang, Yang, Cheng, Xie, Ruobing, Liu, Zhiyuan, Sun, Maosong
The rapid advancement of large language models (LLMs) has paved the way for the development of highly capable autonomous agents. However, existing multi-agent frameworks often struggle with integrating diverse capable third-party agents due to relian
Externí odkaz:
http://arxiv.org/abs/2407.07061
Autor:
Wang, Liqiang, Li, Ran
We initiate the study of the information paradox of rotating Kerr black holes by employing the recently proposed island rule. It is known that the scalar field theory near the Kerr black hole horizon can be reduced to the 2-dimensional effective theo
Externí odkaz:
http://arxiv.org/abs/2406.13949
We study the fidelity of information retrieval in the black hole final state model by taking into account the interactions between the collapsing matter and the infalling Hawking radiation inside the event horizon. By utilizing a scrambling unitary o
Externí odkaz:
http://arxiv.org/abs/2406.09673