Zobrazeno 1 - 10
of 4 632
pro vyhledávání: '"Chen, Quan"'
Autor:
Liu, Shengyuan, Wang, Bo, Ma, Ye, Yang, Te, Cao, Xipeng, Chen, Quan, Li, Han, Dong, Di, Jiang, Peng
Existing subject-driven text-to-image generation models suffer from tedious fine-tuning steps and struggle to maintain both text-image alignment and subject fidelity. For generating compositional subjects, it often encounters problems such as object
Externí odkaz:
http://arxiv.org/abs/2405.06948
Autor:
Jia, Jian, Wang, Yipei, Li, Yan, Chen, Honggang, Bai, Xuehan, Liu, Zhaocheng, Liang, Jian, Chen, Quan, Li, Han, Jiang, Peng, Gai, Kun
Contemporary recommender systems predominantly rely on collaborative filtering techniques, employing ID-embedding to capture latent associations among users and items. However, this approach overlooks the wealth of semantic information embedded withi
Externí odkaz:
http://arxiv.org/abs/2405.03988
Autor:
Zhao, Han, Cui, Weihao, Chen, Quan, Zhang, Shulai, Li, Zijun, Leng, Jingwen, Li, Chao, Zeng, Deze, Guo, Minyi
Integrating GPUs into serverless computing platforms is crucial for improving efficiency. However, existing solutions for GPU-enabled serverless computing platforms face two significant problems due to coarse-grained GPU management: long setup time a
Externí odkaz:
http://arxiv.org/abs/2404.14691
Autor:
Xue, Chunyu, Cui, Weihao, Zhao, Han, Chen, Quan, Zhang, Shulai, Yang, Pengyu, Yang, Jing, Li, Shaobo, Guo, Minyi
Joint consideration of scheduling and adaptive parallelism offers great opportunities for improving the training efficiency of large models on heterogeneous GPU clusters. However, integrating adaptive parallelism into a cluster scheduler expands the
Externí odkaz:
http://arxiv.org/abs/2403.16125
Autor:
Zhang, Qianyu, Zheng, Bolun, Chen, Xinying, Chen, Quan, Zhu, Zhunjie, Wang, Canjin, Li, Zongpeng, Yan, Chengang
Video compression artifacts arise due to the quantization operation in the frequency domain. The goal of video quality enhancement is to reduce compression artifacts and reconstruct a visually-pleasant result. In this work, we propose a hierarchical
Externí odkaz:
http://arxiv.org/abs/2403.11556
Autor:
Jing, Xu, Qian, Cheng, Weng, Chen-Xun, Li, Bing-Hong, Chen, Zhe, Wang, Chen-Quan, Tang, Jie, Gu, Xiao-Wen, Kong, Yue-Chan, Chen, Tang-Sheng, Yin, Hua-Lei, Jiang, Dong, Niu, Bin, Lu, Liang-Liang
Quantum communication networks are crucial for both secure communication and cryptographic networked tasks. Building quantum communication networks in a scalable and cost-effective way is essential for their widespread adoption, among which a stable
Externí odkaz:
http://arxiv.org/abs/2403.11441
Autor:
Hao, Dongze, Jia, Jian, Guo, Longteng, Wang, Qunbo, Yang, Te, Li, Yan, Cheng, Yanhua, Wang, Bo, Chen, Quan, Li, Han, Liu, Jing
Knowledge-based visual question answering (KB-VQA) is a challenging task, which requires the model to leverage external knowledge for comprehending and answering questions grounded in visual content. Recent studies retrieve the knowledge passages fro
Externí odkaz:
http://arxiv.org/abs/2403.10037
Autor:
Chen, Quan, Wang, Tingyu, Yang, Zihao, Li, Haoran, Lu, Rongfeng, Sun, Yaoqi, Zheng, Bolun, Yan, Chenggang
Cross-view geo-localization aims to match images of the same target from different platforms, e.g., drone and satellite. It is a challenging task due to the changing both appearance of targets and environmental content from different views. Existing
Externí odkaz:
http://arxiv.org/abs/2403.04172
Lung cancer is a devastating disease with the highest mortality rate among cancer types. Over 60% of non-small cell lung cancer (NSCLC) patients, which accounts for 87% of diagnoses, require radiation therapy. Rapid treatment initiation significantly
Externí odkaz:
http://arxiv.org/abs/2402.14099
Autor:
Guo, Cong, Xue, Fengchen, Leng, Jingwen, Qiu, Yuxian, Guan, Yue, Cui, Weihao, Chen, Quan, Guo, Minyi
Network pruning can reduce the computation cost of deep neural network (DNN) models. However, sparse models often produce randomly-distributed weights to maintain accuracy, leading to irregular computations. Consequently, unstructured sparse models c
Externí odkaz:
http://arxiv.org/abs/2402.10876