Zobrazeno 1 - 10
of 172
pro vyhledávání: '"SONG Ruihua"'
Publikováno v:
发电技术, Vol 43, Iss 1, Pp 111-118 (2022)
In order to evaluate the temporary overvoltage level of the wind power transmission system based on permanent magnet synchronous generator (PMSG) in case of load rejection, it is necessary to clarify the temporary overvoltage characteristics and its
Externí odkaz:
https://doaj.org/article/3836804fe0ac4d80b952894113c9074e
Retrieval Augmented Generation (RAG) system is important in domains such as e-commerce, which has many long-tail entities and frequently updated information. Most existing works adopt separate modules for retrieval and generation, which may be subopt
Externí odkaz:
http://arxiv.org/abs/2409.20075
Autor:
Shi, Jiatong, Tian, Jinchuan, Wu, Yihan, Jung, Jee-weon, Yip, Jia Qi, Masuyama, Yoshiki, Chen, William, Wu, Yuning, Tang, Yuxun, Baali, Massa, Alharhi, Dareen, Zhang, Dong, Deng, Ruifan, Srivastava, Tejes, Wu, Haibin, Liu, Alexander H., Raj, Bhiksha, Jin, Qin, Song, Ruihua, Watanabe, Shinji
Neural codecs have become crucial to recent speech and audio generation research. In addition to signal compression capabilities, discrete codecs have also been found to enhance downstream training efficiency and compatibility with autoregressive lan
Externí odkaz:
http://arxiv.org/abs/2409.15897
Video-to-audio (V2A) generation is important for video editing and post-processing, enabling the creation of semantics-aligned audio for silent video. However, most existing methods focus on generating short-form audio for short video segment (less t
Externí odkaz:
http://arxiv.org/abs/2409.15157
Visual signals can enhance audiovisual speech recognition accuracy by providing additional contextual information. Given the complexity of visual signals, an audiovisual speech recognition model requires robust generalization capabilities across dive
Externí odkaz:
http://arxiv.org/abs/2409.12370
Image captioning, which generates natural language descriptions of the visual information in an image, is a crucial task in vision-language research. Previous models have typically addressed this task by aligning the generative capabilities of machin
Externí odkaz:
http://arxiv.org/abs/2408.16809
Autor:
Chen, Jie, Chen, Zhipeng, Wang, Jiapeng, Zhou, Kun, Zhu, Yutao, Jiang, Jinhao, Min, Yingqian, Zhao, Wayne Xin, Dou, Zhicheng, Mao, Jiaxin, Lin, Yankai, Song, Ruihua, Xu, Jun, Chen, Xu, Yan, Rui, Wei, Zhewei, Hu, Di, Huang, Wenbing, Wen, Ji-Rong
Continual pre-training (CPT) has been an important approach for adapting language models to specific domains or tasks. To make the CPT approach more traceable, this paper presents a technical report for continually pre-training Llama-3 (8B), which si
Externí odkaz:
http://arxiv.org/abs/2407.18743
Publikováno v:
Di-san junyi daxue xuebao, Vol 42, Iss 7, Pp 678-683 (2020)
Objective To investigate the effect of IL-2 on CD4+ regulatory cells (Treg) in inflammatory bowel disease (IBD) mice induced by dextran sulfate sodium (DSS), and to explore its regulatory mechanism in the pathogenesis of IBD. Methods Wild type C57BL/
Externí odkaz:
https://doaj.org/article/84965bd116484bd6995d253895f1c041
Autor:
Zhu, Yutao, Zhou, Kun, Mao, Kelong, Chen, Wentong, Sun, Yiding, Chen, Zhipeng, Cao, Qian, Wu, Yihan, Chen, Yushuo, Wang, Feng, Zhang, Lei, Li, Junyi, Wang, Xiaolei, Wang, Lei, Zhang, Beichen, Dong, Zican, Cheng, Xiaoxue, Chen, Yuhan, Tang, Xinyu, Hou, Yupeng, Ren, Qiangqiang, Pang, Xincheng, Xie, Shufang, Zhao, Wayne Xin, Dou, Zhicheng, Mao, Jiaxin, Lin, Yankai, Song, Ruihua, Xu, Jun, Chen, Xu, Yan, Rui, Wei, Zhewei, Hu, Di, Huang, Wenbing, Gao, Ze-Feng, Chen, Yueguo, Lu, Weizheng, Wen, Ji-Rong
Large language models (LLMs) have become the foundation of many applications, leveraging their extensive capabilities in processing and understanding natural language. While many open-source LLMs have been released with technical reports, the lack of
Externí odkaz:
http://arxiv.org/abs/2406.19853
Modeling generalized robot control policies poses ongoing challenges for language-guided robot manipulation tasks. Existing methods often struggle to efficiently utilize cross-dataset resources or rely on resource-intensive vision-language models, th
Externí odkaz:
http://arxiv.org/abs/2403.07312