Zobrazeno 1 - 10
of 26 552
pro vyhledávání: '"CHEN, Bo"'
Autor:
Chen, Bo
Conversational recommender systems (CRSs) aim to capture user preferences and provide personalized recommendations through multi-round natural language dialogues. However, most existing CRS models mainly focus on dialogue comprehension and preference
Externí odkaz:
http://arxiv.org/abs/2407.04960
Large language models have been flourishing in the natural language processing (NLP) domain, and their potential for recommendation has been paid much attention to. Despite the intelligence shown by the recommendation-oriented finetuned models, LLMs
Externí odkaz:
http://arxiv.org/abs/2406.18825
This letter devises an AI-Inverter that pilots the use of a physics-informed neural network (PINN) to enable AI-based electromagnetic transient simulations (EMT) of grid-forming inverters. The contributions are threefold: (1) A PINN-enabled AI-Invert
Externí odkaz:
http://arxiv.org/abs/2406.17661
Autor:
Chen, Bo, Song, Chong
In this paper, we derive decay estimates near isolated singularities of 3-dimensional (3d) Yang-Mills-Higgs fields defined on a fiber bundle, where the fiber space is a compact Riemannian manifold and the structure group is a connected compact Lie gr
Externí odkaz:
http://arxiv.org/abs/2406.16276
Autor:
Wu, Mingyuan, Liu, Zichuan, Zheng, Haozhen, Guo, Hongpeng, Chen, Bo, Lu, Xin, Nahrstedt, Klara
Efficient single instance segmentation is essential for unlocking features in the mobile imaging applications, such as capture or editing. Existing on-the-fly mobile imaging applications scope the segmentation task to portraits or the salient subject
Externí odkaz:
http://arxiv.org/abs/2406.14874
Self-ensemble adversarial training methods improve model robustness by ensembling models at different training epochs, such as model weight averaging (WA). However, previous research has shown that self-ensemble defense methods in adversarial trainin
Externí odkaz:
http://arxiv.org/abs/2406.14259
Autor:
Gao, Jingtong, Chen, Bo, Zhao, Xiangyu, Liu, Weiwen, Li, Xiangyang, Wang, Yichao, Zhang, Zijian, Wang, Wanyu, Ye, Yuyang, Lin, Shanru, Guo, Huifeng, Tang, Ruiming
Reranking is a critical component in recommender systems, playing an essential role in refining the output of recommendation algorithms. Traditional reranking models have focused predominantly on accuracy, but modern applications demand consideration
Externí odkaz:
http://arxiv.org/abs/2406.12433
Autor:
Xue, Jianchao, Feng, Li, Li, Hui, Zhang, Ping, Chen, Jun, Shi, Guanglu, Ji, Kaifan, Qiu, Ye, Li, Chuan, Lu, Lei, Ying, Beili, Li, Ying, Huang, Yu, Li, Youping, Li, Jingwei, Zhao, Jie, Song, Dechao, Li, Shuting, Tian, Zhengyuan, Su, Yingna, Zhang, Qingmin, Ge, Yunyi, Shan, Jiahui, Li, Qiao, Li, Gen, Zhou, Yue, Tian, Jun, Liu, Xiaofeng, Jing, Zhichen, Chen, Bo, Song, Kefei, He, Lingping, Lei, Shijun, Gan, Weiqun
Sympathetic eruptions of solar prominences have been studied for decades, however, it is usually difficult to identify their causal links. Here we present two failed prominence eruptions on 26 October 2022 and explore their connections. Using stereos
Externí odkaz:
http://arxiv.org/abs/2406.11602
In this paper, an anti-eavesdropping estimation problem is investigated. A linear encryption scheme is utilized, which first linearly transforms innovation via an encryption matrix and then encrypts some components of the transformed innovation. To r
Externí odkaz:
http://arxiv.org/abs/2406.10677