Zobrazeno 1 - 10
of 11 082
pro vyhledávání: '"An, Yuansheng"'
Autor:
Xie, Xiangzhi, Feng, Hanke, Tao, Yuansheng, Zhang, Yiwen, Chen, Yikun, Zhang, Ke, Chen, Zhaoxi, Wang, Cheng
Frequency mixers are fundamental components in modern wireless communication and radar systems, responsible for up- and down-conversion of target radio-frequency (RF) signals. Recently, photonic-assisted RF mixers have shown unique advantages over tr
Externí odkaz:
http://arxiv.org/abs/2410.12426
Autor:
Chen, Jiacheng, Liang, Tianhao, Siu, Sherman, Wang, Zhengqing, Wang, Kai, Wang, Yubo, Ni, Yuansheng, Zhu, Wang, Jiang, Ziyan, Lyu, Bohan, Jiang, Dongfu, He, Xuan, Liu, Yuan, Hu, Hexiang, Yue, Xiang, Chen, Wenhu
We present MEGA-Bench, an evaluation suite that scales multimodal evaluation to over 500 real-world tasks, to address the highly heterogeneous daily use cases of end users. Our objective is to optimize for a set of high-quality data samples that cove
Externí odkaz:
http://arxiv.org/abs/2410.10563
Given a graph $G$ with vertex set $V$, an outer independent Roman dominating function (OIRDF) is a function $f$ from $V(G)$ to $\{0, 1, 2\}$ for which every vertex with label $0$ under $f$ is adjacent to at least a vertex with label $2$ but not adjac
Externí odkaz:
http://arxiv.org/abs/2410.06486
Visual language pre-training (VLP) models have demonstrated significant success across various domains, yet they remain vulnerable to adversarial attacks. Addressing these adversarial vulnerabilities is crucial for enhancing security in multimodal le
Externí odkaz:
http://arxiv.org/abs/2410.04884
Autor:
Lim, Soon Wei Daniel, Kee, Yong How, Smith, Scott Nicholas Allan, Tan, Shan Mei, Lim, An Eng, Yang, Yuansheng, Goh, Shireen
Inertial microfluidics have been limited to dilute particle concentrations due to defocusing at high particle concentrations. However, we observed a counterintuitive shift of focusing to the outer wall at high concentrations, which contradicts the ex
Externí odkaz:
http://arxiv.org/abs/2409.12488
Autor:
Yue, Xiang, Zheng, Tianyu, Ni, Yuansheng, Wang, Yubo, Zhang, Kai, Tong, Shengbang, Sun, Yuxuan, Yu, Botao, Zhang, Ge, Sun, Huan, Su, Yu, Chen, Wenhu, Neubig, Graham
This paper introduces MMMU-Pro, a robust version of the Massive Multi-discipline Multimodal Understanding and Reasoning (MMMU) benchmark. MMMU-Pro rigorously assesses multimodal models' true understanding and reasoning capabilities through a three-st
Externí odkaz:
http://arxiv.org/abs/2409.02813
Autor:
He, Xuan, Jiang, Dongfu, Zhang, Ge, Ku, Max, Soni, Achint, Siu, Sherman, Chen, Haonan, Chandra, Abhranil, Jiang, Ziyan, Arulraj, Aaran, Wang, Kai, Do, Quy Duc, Ni, Yuansheng, Lyu, Bohan, Narsupalli, Yaswanth, Fan, Rongqi, Lyu, Zhiheng, Lin, Yuchen, Chen, Wenhu
The recent years have witnessed great advances in video generation. However, the development of automatic video metrics is lagging significantly behind. None of the existing metric is able to provide reliable scores over generated videos. The main ba
Externí odkaz:
http://arxiv.org/abs/2406.15252
Autor:
Si, Dawei, Xiao, Sheng, Qin, Yuhao, Wang, Yijie, Xu, Junhuai, Tian, Baiting, Zhang, Boyuan, Guo, Dong, Zhi, Qin, Wei, Xiaobao, Hao, Yibo, Wang, Zengxiang, Zhuo, Tianren, Yang, Yuansheng, Wei, Xianglun, Yang, Herun, Ma, Peng, Duan, Limin, Duan, Fangfang, Ma, Junbing, Xu, Shiwei, Bai, Zhen, Yang, Guo, Yang, Yanyun, Xiao, Zhigang
The emission of neutrons from heavy ion reactions is an important observable for studying the asymmetric nuclear equation of state and the reaction dynamics. A 20-unit neutron array has been developed and mounted on the compact spectrometer for heavy
Externí odkaz:
http://arxiv.org/abs/2406.18605
Autor:
Liu, Ziqiang, Fang, Feiteng, Feng, Xi, Du, Xinrun, Zhang, Chenhao, Wang, Zekun, Bai, Yuelin, Zhao, Qixuan, Fan, Liyang, Gan, Chengguang, Lin, Hongquan, Li, Jiaming, Ni, Yuansheng, Wu, Haihong, Narsupalli, Yaswanth, Zheng, Zhigang, Li, Chengming, Hu, Xiping, Xu, Ruifeng, Chen, Xiaojun, Yang, Min, Liu, Jiaheng, Liu, Ruibo, Huang, Wenhao, Zhang, Ge, Ni, Shiwen
The rapid advancements in the development of multimodal large language models (MLLMs) have consistently led to new breakthroughs on various benchmarks. In response, numerous challenging and comprehensive benchmarks have been proposed to more accurate
Externí odkaz:
http://arxiv.org/abs/2406.05862
Generative AI has made remarkable strides to revolutionize fields such as image and video generation. These advancements are driven by innovative algorithms, architecture, and data. However, the rapid proliferation of generative models has highlighte
Externí odkaz:
http://arxiv.org/abs/2406.04485