Zobrazeno 1 - 10
of 94 713
pro vyhledávání: '"YUJIE AN"'
Autor:
Pishehvar, Amin, Wang, Zhaoyou, Zhu, Yujie, Jiang, Yu, Yan, Zixin, Li, Fangxin, Jornet, Josep M., Hu, Jia-Mian, Jiang, Liang, Zhang, Xufeng
Cavity magnonics is a promising field focusing the interaction between spin waves (magnons) and other types of signals. In cavity magnonics, the function of isolating magnons from the cavity to allow signal storage and processing fully in the magnoni
Externí odkaz:
http://arxiv.org/abs/2412.15600
Inductive Knowledge Graph Completion (KGC) aims to infer missing facts between newly emerged entities within knowledge graphs (KGs), posing a significant challenge. While recent studies have shown promising results in inferring such entities through
Externí odkaz:
http://arxiv.org/abs/2412.15822
Autor:
Mao, Qianren, Luo, Yangyifei, Zhang, Jinlong, Hao, Hanwen, Cao, Zhilong, Wang, Xiaolong, Guan, Xiao, Huang, Zhenting, Jiang, Weifeng, Guo, Shuyu, Han, Zhentao, Zhang, Qili, Tao, Siyuan, Liu, Yujie, Liu, Junnan, Tan, Zhixing, Sun, Jie, Li, Bo, Liu, Xudong, Zhang, Richong, Li, Jianxin
Retrieval-augmented generation (RAG) synergizes the retrieval of pertinent data with the generative capabilities of Large Language Models (LLMs), ensuring that the generated output is not only contextually relevant but also accurate and current.We in
Externí odkaz:
http://arxiv.org/abs/2412.15529
Skeleton-based action recognition using GCNs has achieved remarkable performance, but recognizing ambiguous actions, such as "waving" and "saluting", remains a significant challenge. Existing methods typically rely on a serial combination of GCNs and
Externí odkaz:
http://arxiv.org/abs/2412.14833
Boosted by Multi-modal Large Language Models (MLLMs), text-guided universal segmentation models for the image and video domains have made rapid progress recently. However, these methods are often developed separately for specific domains, overlooking
Externí odkaz:
http://arxiv.org/abs/2412.14006
Autor:
Guo, Wuzheng, Wang, Qiumin, Cao, Shuo, Biesiada, Marek, Liu, Tonghua, Lian, Yujie, Jiang, Xinyue, Mu, Chengsheng, Cheng, Dadian
In this Letter, we use the latest results from the Dark Energy Spectroscopic Instrument (DESI) survey to measure the Hubble constant. Baryon acoustic oscillation (BAO) observations released by the DESI survey, allow us to determine $H_0$ from the fir
Externí odkaz:
http://arxiv.org/abs/2412.13045
Graph Neural Networks (GNNs) perform effectively when training and testing graphs are drawn from the same distribution, but struggle to generalize well in the face of distribution shifts. To address this issue, existing mainstreaming graph rationaliz
Externí odkaz:
http://arxiv.org/abs/2412.12880
Autor:
Chen, Yujie, Yi, Jiangyan, Fan, Cunhang, Tao, Jianhua, Ren, Yong, Zeng, Siding, Zhang, Chu Yuan, Yan, Xinrui, Gu, Hao, Xue, Jun, Wang, Chenglong, Lv, Zhao, Zhang, Xiaohui
Rapid advancements in speech synthesis and voice conversion bring convenience but also new security risks, creating an urgent need for effective audio deepfake detection. Although current models perform well, their effectiveness diminishes when confr
Externí odkaz:
http://arxiv.org/abs/2412.11551
Efficient Quantization-Aware Training on Segment Anything Model in Medical Images and Its Deployment
Medical image segmentation is a critical component of clinical practice, and the state-of-the-art MedSAM model has significantly advanced this field. Nevertheless, critiques highlight that MedSAM demands substantial computational resources during inf
Externí odkaz:
http://arxiv.org/abs/2412.11186
Text-to-3D generation has achieved remarkable progress in recent years, yet evaluating these methods remains challenging for two reasons: i) Existing benchmarks lack fine-grained evaluation on different prompt categories and evaluation dimensions. ii
Externí odkaz:
http://arxiv.org/abs/2412.11170