Zobrazeno 1 - 10
of 585 614
pro vyhledávání: '"Bing, A."'
The Radcliffe wave \cite{2020Natur.578..237A} is a 2.7 kpc long, 100 pc wide-like structure in the Galactic disk with a wave-like velocity structure \cite{2022MNRAS.517L.102L,2024arXiv240212596K}. A referent Nature paper \cite{2024arXiv240212596K} tr
Externí odkaz:
http://arxiv.org/abs/2410.14603
Autor:
Zhou, Zi-Min, Wang, Xiang-Gao, Liang, En-Wei, Cao, Jia-Xin, Liu, Hui-Ya, Li, Cheng-Kui, Li, Bing, Lin, Da-Bin, Zheng, Tian-Ci, Lu, Rui-Jing
Publikováno v:
2024, apj, 972, 190.
Power Density Spectrum (PDS) is one of the powerful tools to study light curves of gamma-ray bursts (GRBs). We show the average PDS and individual PDS analysis with {\it Hard X-ray Modulation Telescope} (also named \insighthxmt) GRBs data. The values
Externí odkaz:
http://arxiv.org/abs/2410.14119
Recent studies have revealed that GNNs are highly susceptible to multiple adversarial attacks. Among these, graph backdoor attacks pose one of the most prominent threats, where attackers cause models to misclassify by learning the backdoored features
Externí odkaz:
http://arxiv.org/abs/2410.14105
Autor:
Narendra, Aditya, Dainotti, Maria, Sarkar, Milind, Lenart, Aleksander, Bogdan, Malgorzata, Pollo, Agnieszka, Zhang, Bing, Rabeda, Aleksandra, Petrosian, Vahe, Kazunari, Iwasaki
Context. Gamma-ray bursts (GRBs), observed at redshifts as high as 9.4, could serve as valuable probes for investigating the distant Universe. However, this necessitates an increase in the number of GRBs with determined redshifts, as currently, only
Externí odkaz:
http://arxiv.org/abs/2410.13985
Large Language Models (LLMs) have achieved impressive results across numerous NLP tasks but still encounter difficulties in machine translation. Traditional methods to improve translation have typically involved fine-tuning LLMs using parallel corpor
Externí odkaz:
http://arxiv.org/abs/2410.13944
Autor:
Huang, Lei, Feng, Xiaocheng, Ma, Weitao, Zhao, Liang, Fan, Yuchun, Zhong, Weihong, Xu, Dongliang, Yang, Qing, Liu, Hongtao, Qin, Bing
Teaching large language models (LLMs) to generate text with citations to evidence sources can mitigate hallucinations and enhance verifiability in information-seeking systems. However, improving this capability requires high-quality attribution data,
Externí odkaz:
http://arxiv.org/abs/2410.13298
We consider the spatially inhomogeneous Boltzmann equation without angular cutoff for soft potentials. For any given initial datum such that the mass, energy and entropy densities are bounded and the mass is away from vacuum, we establish the local-i
Externí odkaz:
http://arxiv.org/abs/2410.13205
Autor:
Li, Long, Xu, Weiwen, Guo, Jiayan, Zhao, Ruochen, Li, Xinxuan, Yuan, Yuqian, Zhang, Boqiang, Jiang, Yuming, Xin, Yifei, Dang, Ronghao, Zhao, Deli, Rong, Yu, Feng, Tian, Bing, Lidong
Effective research ideation is a critical step for scientific research. However, the exponential increase in scientific literature makes it challenging for researchers to stay current with recent advances and identify meaningful research directions.
Externí odkaz:
http://arxiv.org/abs/2410.13185
Autor:
Leng, Sicong, Xing, Yun, Cheng, Zesen, Zhou, Yang, Zhang, Hang, Li, Xin, Zhao, Deli, Lu, Shijian, Miao, Chunyan, Bing, Lidong
Recent advancements in large multimodal models (LMMs) have significantly enhanced performance across diverse tasks, with ongoing efforts to further integrate additional modalities such as video and audio. However, most existing LMMs remain vulnerable
Externí odkaz:
http://arxiv.org/abs/2410.12787
Latent-based image generative models, such as Latent Diffusion Models (LDMs) and Mask Image Models (MIMs), have achieved notable success in image generation tasks. These models typically leverage reconstructive autoencoders like VQGAN or VAE to encod
Externí odkaz:
http://arxiv.org/abs/2410.12490