Zobrazeno 1 - 10
of 586
pro vyhledávání: '"Liu Yunxin"'
Autor:
Mi, Liang, Wang, Weijun, Tu, Wenming, He, Qingfeng, Kong, Rui, Fang, Xinyu, Dong, Yazhu, Zhang, Yikang, Li, Yunchun, Li, Meng, Dai, Haipeng, Chen, Guihai, Liu, Yunxin
Large Multimodal Models (LMMs) have shown significant progress in various complex vision tasks with the solid linguistic and reasoning capacity inherited from large language models (LMMs). Low-rank adaptation (LoRA) offers a promising method to integ
Externí odkaz:
http://arxiv.org/abs/2411.00915
Autor:
Fang Xianjun, Xian Xirui, Tang Jie, Mu Huiwen, Zheng Shaojun, Ling Qiaoyun, Liu Yunxin, Sun Xuqun
Publikováno v:
Journal of Pharmacological Sciences, Vol 146, Iss 4, Pp 249-258 (2021)
Momordin Ic (MI) is a natural pentacyclic triterpenoid enriched in various Chinese natural medicines such as the fruit of Kochia scoparia (L.) Schrad. Studies have shown that MI presents antitumor properties in liver and prostate cancers. However, th
Externí odkaz:
https://doaj.org/article/0d05a15faed94d9798ffa1058bd95f1f
Imitation based robot learning has recently gained significant attention in the robotics field due to its theoretical potential for transferability and generalizability. However, it remains notoriously costly, both in terms of hardware and data colle
Externí odkaz:
http://arxiv.org/abs/2409.12061
Running LLMs on end devices has garnered significant attention recently due to their advantages in privacy preservation. With the advent of lightweight LLM models and specially designed GPUs, on-device LLM inference has achieved the necessary accurac
Externí odkaz:
http://arxiv.org/abs/2409.04040
Video analytics is widespread in various applications serving our society. Recent advances of content enhancement in video analytics offer significant benefits for the bandwidth saving and accuracy improvement. However, existing content-enhanced vide
Externí odkaz:
http://arxiv.org/abs/2407.16990
In evaluating the long-context capabilities of large language models (LLMs), identifying content relevant to a user's query from original long documents is a crucial prerequisite for any LLM to answer questions based on long text. We present NeedleBe
Externí odkaz:
http://arxiv.org/abs/2407.11963
Publikováno v:
Jisuanji kexue yu tansuo, Vol 14, Iss 5, Pp 861-869 (2020)
The fast arbitrary style transfer based on meta-networks has attracted great attention and high praise. However, visible gray blocks of stylistic incongruity often appear in stylized result image. The hue of stylized result image is often not consist
Externí odkaz:
https://doaj.org/article/b77006eafd4f4a6286dabe688387398f
Autor:
Kong, Rui, Li, Qiyang, Fang, Xinyu, Feng, Qingtian, He, Qingfeng, Dong, Yazhu, Wang, Weijun, Li, Yuanchun, Kong, Linghe, Liu, Yunxin
Recent literature has found that an effective method to customize or further improve large language models (LLMs) is to add dynamic adapters, such as low-rank adapters (LoRA) with Mixture-of-Experts (MoE) structures. Though such dynamic adapters incu
Externí odkaz:
http://arxiv.org/abs/2405.17741
Autor:
Xu, Mengwei, Yin, Wangsong, Cai, Dongqi, Yi, Rongjie, Xu, Daliang, Wang, Qipeng, Wu, Bingyang, Zhao, Yihao, Yang, Chen, Wang, Shihe, Zhang, Qiyang, Lu, Zhenyan, Zhang, Li, Wang, Shangguang, Li, Yuanchun, Liu, Yunxin, Jin, Xin, Liu, Xuanzhe
Large foundation models, including large language models (LLMs), vision transformers (ViTs), diffusion, and LLM-based multimodal models, are revolutionizing the entire machine learning lifecycle, from training to deployment. However, the substantial
Externí odkaz:
http://arxiv.org/abs/2401.08092
Autor:
Li, Yuanchun, Wen, Hao, Wang, Weijun, Li, Xiangyu, Yuan, Yizhen, Liu, Guohong, Liu, Jiacheng, Xu, Wenxing, Wang, Xiang, Sun, Yi, Kong, Rui, Wang, Yile, Geng, Hanfei, Luan, Jian, Jin, Xuefeng, Ye, Zilong, Xiong, Guanjing, Zhang, Fan, Li, Xiang, Xu, Mengwei, Li, Zhijun, Li, Peng, Liu, Yang, Zhang, Ya-Qin, Liu, Yunxin
Since the advent of personal computing devices, intelligent personal assistants (IPAs) have been one of the key technologies that researchers and engineers have focused on, aiming to help users efficiently obtain information and execute tasks, and pr
Externí odkaz:
http://arxiv.org/abs/2401.05459