Zobrazeno 1 - 10
of 3 867
pro vyhledávání: '"P Boya"'
Autor:
Wang, Xinlong, Zhang, Xiaosong, Luo, Zhengxiong, Sun, Quan, Cui, Yufeng, Wang, Jinsheng, Zhang, Fan, Wang, Yueze, Li, Zhen, Yu, Qiying, Zhao, Yingli, Ao, Yulong, Min, Xuebin, Li, Tao, Wu, Boya, Zhao, Bo, Zhang, Bowen, Wang, Liangdong, Liu, Guang, He, Zheqi, Yang, Xi, Liu, Jingjing, Lin, Yonghua, Huang, Tiejun, Wang, Zhongyuan
While next-token prediction is considered a promising path towards artificial general intelligence, it has struggled to excel in multimodal tasks, which are still dominated by diffusion models (e.g., Stable Diffusion) and compositional approaches (e.
Externí odkaz:
http://arxiv.org/abs/2409.18869
Holographic multiple-input-multiple output (HMIMO), which is enabled by large-scale antenna arrays with quasi-continuous apertures, is expected to be an important technology in the forthcoming 6G wireless network. Reconfigurable intelligent surface (
Externí odkaz:
http://arxiv.org/abs/2409.00298
Autor:
Zhang, Shuhang, Liu, Qingyu, Chen, Ke, Di, Boya, Zhang, Hongliang, Yang, Wenhan, Niyato, Dusit, Han, Zhu, Poor, H. Vincent
The future sixth-generation (6G) of wireless networks is expected to surpass its predecessors by offering ubiquitous coverage through integrated air-ground facility deployments in both communication and computing domains. In this network, aerial faci
Externí odkaz:
http://arxiv.org/abs/2408.04927
Holographic MIMO communications, enabled by large-scale antenna arrays with quasi-continuous apertures, is a potential technology for spectrum efficiency improvement. However, the increased antenna aperture size extends the range of the Fresnel regio
Externí odkaz:
http://arxiv.org/abs/2407.12264
Out-of-distribution (OOD) detection is crucial for the safe deployment of neural networks. Existing CLIP-based approaches perform OOD detection by devising novel scoring functions or sophisticated fine-tuning methods. In this work, we propose SeTAR,
Externí odkaz:
http://arxiv.org/abs/2406.12629
The sparse dictionary coding framework represents signals as a linear combination of a few predefined dictionary atoms. It has been employed for images, time series, graph signals and recently for 2-way (or 2D) spatio-temporal data employing jointly
Externí odkaz:
http://arxiv.org/abs/2406.06960
Autor:
Zhou, Junjie, Shu, Yan, Zhao, Bo, Wu, Boya, Xiao, Shitao, Yang, Xi, Xiong, Yongping, Zhang, Bo, Huang, Tiejun, Liu, Zheng
The evaluation of Long Video Understanding (LVU) performance poses an important but challenging research problem. Despite previous efforts, the existing video understanding benchmarks are severely constrained by several issues, especially the insuffi
Externí odkaz:
http://arxiv.org/abs/2406.04264
The conditional mean embedding (CME) encodes Markovian stochastic kernels through their actions on probability distributions embedded within the reproducing kernel Hilbert spaces (RKHS). The CME plays a key role in several well-known machine learning
Externí odkaz:
http://arxiv.org/abs/2405.07432
Autor:
Yazdani, Anthony, Bornet, Alban, Khlebnikov, Philipp, Zhang, Boya, Rouhizadeh, Hossein, Amini, Poorya, Teodoro, Douglas
Adverse drug events (ADEs) significantly impact clinical research, causing many clinical trial failures. ADE prediction is key for developing safer medications and enhancing patient outcomes. To support this effort, we introduce CT-ADE, a dataset for
Externí odkaz:
http://arxiv.org/abs/2404.12827
Multimodal Large Language Models (MLLMs) have demonstrated notable capabilities in general visual understanding and reasoning tasks. However, their deployment is hindered by substantial computational costs in both training and inference, limiting acc
Externí odkaz:
http://arxiv.org/abs/2402.11530