Zobrazeno 1 - 10
of 37 790
pro vyhledávání: '"Li, Qing 'an"'
Autor:
Zhang, Zhuofan, Zhu, Ziyu, Li, Pengxiang, Liu, Tengyu, Ma, Xiaojian, Chen, Yixin, Jia, Baoxiong, Huang, Siyuan, Li, Qing
Grounding natural language in physical 3D environments is essential for the advancement of embodied artificial intelligence. Current datasets and models for 3D visual grounding predominantly focus on identifying and localizing objects from static, ob
Externí odkaz:
http://arxiv.org/abs/2408.04034
Autor:
Zhang, Jun, Li, En-Ze, Wang, Ya-Jun, Liu, Bang, Zhang, Li-Hua, Zhang, Zheng-Yuan, Shao, Shi-Yao, Li, Qing, Chen, Han-Chao, Ma, Yu, Han, Tian-Yu, Wang, Qi-Feng, Nan, Jia-Dou, Ying, Yi-Ming, Zhu, Dong-Yang, Shi, Bao-Sen, Ding, Dong-Sheng
The interplay between strong long-range interactions and the coherent driving contribute to the formation of complex patterns, symmetry, and novel phases of matter in many-body systems. However, long-range interactions may induce an additional dissip
Externí odkaz:
http://arxiv.org/abs/2408.03109
Cross-view geo-localization in GNSS-denied environments aims to determine an unknown location by matching drone-view images with the correct geo-tagged satellite-view images from a large gallery. Recent research shows that learning discriminative ima
Externí odkaz:
http://arxiv.org/abs/2408.02408
Previous studies in quantum information have recognized that specific types of noise can encode information in certain applications. However, the role of noise in Quantum Hypothesis Testing (QHT), traditionally assumed to undermine performance and re
Externí odkaz:
http://arxiv.org/abs/2408.02282
Deep neural networks (DNNs) have significantly boosted the performance of many challenging tasks. Despite the great development, DNNs have also exposed their vulnerability. Recent studies have shown that adversaries can manipulate the predictions of
Externí odkaz:
http://arxiv.org/abs/2408.01715
Deep learning, as a vital technique, has sparked a notable revolution in artificial intelligence. As the most representative architecture, Transformers have empowered numerous advanced models, especially the large language models that comprise billio
Externí odkaz:
http://arxiv.org/abs/2408.01129
Despite the photorealistic novel view synthesis (NVS) performance achieved by the original 3D Gaussian splatting (3DGS), its rendering quality significantly degrades with sparse input views. This performance drop is mainly caused by the limited numbe
Externí odkaz:
http://arxiv.org/abs/2408.00254
Neural networks are increasingly evolving towards training large models with big data, a method that has demonstrated superior performance across many tasks. However, this approach introduces an urgent problem: current deep learning models are predom
Externí odkaz:
http://arxiv.org/abs/2407.21670
This paper addresses the need for improved precision in existing Retrieval-Augmented Generation (RAG) methods that primarily focus on enhancing recall. We propose a multi-layer knowledge pyramid approach within the RAG framework to achieve a better b
Externí odkaz:
http://arxiv.org/abs/2407.21276
Autor:
Zhang, Tianyi, Zhang, Wengyu, Zhang, Xulu, Wu, Jiaxin, Wei, Xiao-Yong, Cao, Jiannong, Li, Qing
Accurate human localization is crucial for various applications, especially in the Metaverse era. Existing high precision solutions rely on expensive, tag-dependent hardware, while vision-based methods offer a cheaper, tag-free alternative. However,
Externí odkaz:
http://arxiv.org/abs/2407.20870