Zobrazeno 1 - 10
of 2 489
pro vyhledávání: '"Li, XinYue"'
Autor:
Li, Xinyue, Chen, Zhenpeng, Zhang, Jie M., Lou, Yiling, Li, Tianlin, Sun, Weisong, Liu, Yang, Liu, Xuanzhe
Large Language Models (LLMs) have become foundational in modern language-driven applications, profoundly influencing daily life. A critical technique in leveraging their potential is role-playing, where LLMs simulate diverse roles to enhance their re
Externí odkaz:
http://arxiv.org/abs/2411.00585
With the rapid development of wearable device technologies, accelerometers can record minute-by-minute physical activity for consecutive days, which provides important insight into a dynamic association between the intensity of physical activity and
Externí odkaz:
http://arxiv.org/abs/2409.03296
Autor:
Wen, Ruoyu, Crowe, Stephanie Elena, Gupta, Kunal, Li, Xinyue, Billinghurst, Mark, Hoermann, Simon, Allan, Dwain, Nassani, Alaeddin, Piumsomboon, Thammathip
Sensitive information detection is crucial in content moderation to maintain safe online communities. Assisting in this traditionally manual process could relieve human moderators from overwhelming and tedious tasks, allowing them to focus solely on
Externí odkaz:
http://arxiv.org/abs/2409.00940
Autor:
Zhang, Zhichao, Li, Xinyue, Sun, Wei, Jia, Jun, Min, Xiongkuo, Zhang, Zicheng, Li, Chunyi, Chen, Zijian, Wang, Puyi, Ji, Zhongpeng, Sun, Fengyu, Jui, Shangling, Zhai, Guangtao
In recent years, artificial intelligence (AI) driven video generation has garnered significant attention due to advancements in stable diffusion and large language model techniques. Thus, there is a great demand for accurate video quality assessment
Externí odkaz:
http://arxiv.org/abs/2407.21408
Autor:
Gao, Shiqi, Duan, Huiyu, Li, Xinyue, Fu, Kang, Peng, Yicong, Xu, Qihang, Chang, Yuanyuan, Wang, Jia, Min, Xiongkuo, Zhai, Guangtao
In recent years, learning-based color and tone enhancement methods for photos have become increasingly popular. However, most learning-based image enhancement methods just learn a mapping from one distribution to another based on one dataset, lacking
Externí odkaz:
http://arxiv.org/abs/2406.15848
This work proposes to augment the lifting steps of the conventional wavelet transform with additional neural network assisted lifting steps. These additional steps reduce residual redundancy (notably aliasing information) amongst the wavelet subbands
Externí odkaz:
http://arxiv.org/abs/2403.01647
Autor:
Shi, Wentao, He, Xiangnan, Zhang, Yang, Gao, Chongming, Li, Xinyue, Zhang, Jizhi, Wang, Qifan, Feng, Fuli
Planning for both immediate and long-term benefits becomes increasingly important in recommendation. Existing methods apply Reinforcement Learning (RL) to learn planning capacity by maximizing cumulative reward for long-term recommendation. However,
Externí odkaz:
http://arxiv.org/abs/2403.00843
This paper provides a comprehensive study on features and performance of different ways to incorporate neural networks into lifting-based wavelet-like transforms, within the context of fully scalable and accessible image compression. Specifically, we
Externí odkaz:
http://arxiv.org/abs/2402.18761
Symmetry, which describes invariance, is an eternal concern in mathematics and physics, especially in the investigation of solutions to the partial differential equation (PDE). A PDE's nonlocally related PDE systems provide excellent approaches to se
Externí odkaz:
http://arxiv.org/abs/2401.14795