Zobrazeno 1 - 10
of 35 547
pro vyhledávání: '"XU, Jing"'
Cavity magnomechanics is one important hybrid magnonic platform that focuses on the coherent interaction between magnons and phonons. The resulting magnon polarons inherit the intrinsic properties of both magnons and phonons, combining their individu
Externí odkaz:
http://arxiv.org/abs/2412.16312
Image restoration (IR) is a long-standing task to recover a high-quality image from its corrupted observation. Recently, transformer-based algorithms and some attention-based convolutional neural networks (CNNs) have presented promising results on se
Externí odkaz:
http://arxiv.org/abs/2412.11008
Autor:
Li, Chuanyu, Dang, Renjun, Li, Xiang, Wu, Zhiyuan, Xu, Jing, Kasaei, Hamidreza, Calandra, Roberto, Lepora, Nathan, Luo, Shan, Su, Hao, Chen, Rui
This article introduces the ManiSkill-ViTac Challenge 2025, which focuses on learning contact-rich manipulation skills using both tactile and visual sensing. Expanding upon the 2024 challenge, ManiSkill-ViTac 2025 includes 3 independent tracks: tacti
Externí odkaz:
http://arxiv.org/abs/2411.12503
Autor:
Prasad, Archiki, Yuan, Weizhe, Pang, Richard Yuanzhe, Xu, Jing, Fazel-Zarandi, Maryam, Bansal, Mohit, Sukhbaatar, Sainbayar, Weston, Jason, Yu, Jane
Self-alignment, whereby models learn to improve themselves without human annotation, is a rapidly growing research area. However, existing techniques often fail to improve complex reasoning tasks due to the difficulty of assigning correct rewards. An
Externí odkaz:
http://arxiv.org/abs/2411.04109
Autor:
Yang, Qifan, Xu, Jing, Fu, Xiao, Lian, Jingchen, Wang, Liqi, Gong, Xuhe, Wang, Zibin, Xiao, Ruijuan, Li, Hong
In solid-state batteries (SSBs), improving the physical contact at the electrode-electrolyte interface is essential for achieving better performance and durability. On the one hand, it is necessary to look for solid-state electrolytes (SSEs) with hig
Externí odkaz:
http://arxiv.org/abs/2410.15350
Autor:
Chen, Kai, Gou, Yunhao, Huang, Runhui, Liu, Zhili, Tan, Daxin, Xu, Jing, Wang, Chunwei, Zhu, Yi, Zeng, Yihan, Yang, Kuo, Wang, Dingdong, Xiang, Kun, Li, Haoyuan, Bai, Haoli, Han, Jianhua, Li, Xiaohui, Jin, Weike, Xie, Nian, Zhang, Yu, Kwok, James T., Zhao, Hengshuang, Liang, Xiaodan, Yeung, Dit-Yan, Chen, Xiao, Li, Zhenguo, Zhang, Wei, Liu, Qun, Yao, Jun, Hong, Lanqing, Hou, Lu, Xu, Hang
GPT-4o, an omni-modal model that enables vocal conversations with diverse emotions and tones, marks a milestone for omni-modal foundation models. However, empowering Large Language Models to perceive and generate images, texts, and speeches end-to-en
Externí odkaz:
http://arxiv.org/abs/2409.18042
Semantic communication technology emerges as a pivotal bridge connecting AI with classical communication. The current semantic communication systems are generally modeled as an Auto-Encoder (AE). AE lacks a deep integration of AI principles with comm
Externí odkaz:
http://arxiv.org/abs/2410.08222
Autor:
Bai, Jieyun, Zhou, Zihao, Ou, Zhanhong, Koehler, Gregor, Stock, Raphael, Maier-Hein, Klaus, Elbatel, Marawan, Martí, Robert, Li, Xiaomeng, Qiu, Yaoyang, Gou, Panjie, Chen, Gongping, Zhao, Lei, Zhang, Jianxun, Dai, Yu, Wang, Fangyijie, Silvestre, Guénolé, Curran, Kathleen, Sun, Hongkun, Xu, Jing, Cai, Pengzhou, Jiang, Lu, Lan, Libin, Ni, Dong, Zhong, Mei, Chen, Gaowen, Campello, Víctor M., Lu, Yaosheng, Lekadir, Karim
Segmentation of the fetal and maternal structures, particularly intrapartum ultrasound imaging as advocated by the International Society of Ultrasound in Obstetrics and Gynecology (ISUOG) for monitoring labor progression, is a crucial first step for
Externí odkaz:
http://arxiv.org/abs/2409.10980
While large language models (LLMs) have been explored in the speech domain for both generation and recognition tasks, their applications are predominantly confined to the monolingual scenario, with limited exploration in multilingual and code-switche
Externí odkaz:
http://arxiv.org/abs/2409.10969
Autor:
Jiang, Taoran, Ma, Liqian, Guan, Yixuan, Meng, Jiaojiao, Chen, Weihang, Zeng, Zecui, Li, Lusong, Wu, Dan, Xu, Jing, Chen, Rui
Articulated object manipulation is ubiquitous in daily life. In this paper, we present DexSim2Real$^{2}$, a novel robot learning framework for goal-conditioned articulated object manipulation using both two-finger grippers and multi-finger dexterous
Externí odkaz:
http://arxiv.org/abs/2409.08750