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pro vyhledávání: '"Wang, Zhipin"'
Autor:
Wang, Zhiping.
Publikováno v:
Sammanfattning på engelska (spikblad).
Diss. Linköping : Univ., 2004.
Externí odkaz:
http://www.bibl.liu.se/liupubl/disp/disp2004/tek889s.pdf
Autor:
Wang, Zhiping
Publikováno v:
Fulltext Online.
Diss. (sammanfattning) Stockholm : Karol. inst.
Härtill 5 uppsatser.
Härtill 5 uppsatser.
Externí odkaz:
http://diss.kib.ki.se/1997/91-7045-445-0
http://ebib.arbetslivsinstitutet.se/ah/1997/ah1997_23.pdf
http://ebib.arbetslivsinstitutet.se/ah/1997/ah1997_23.pdf
Autor:
Wang, Zhiping.
This study addresses the synchronization problem that arises during the application of a predetermined test sequence in some test architectures used for protocol conformance testing. A solution to this problem is to construct synchronizable test sequ
Externí odkaz:
http://hdl.handle.net/10393/7589
Autor:
Shi, Zhelun, Wang, Zhipin, Fan, Hongxing, Zhang, Zaibin, Li, Lijun, Zhang, Yongting, Yin, Zhenfei, Sheng, Lu, Qiao, Yu, Shao, Jing
Large Language Models (LLMs) aim to serve as versatile assistants aligned with human values, as defined by the principles of being helpful, honest, and harmless (hhh). However, in terms of Multimodal Large Language Models (MLLMs), despite their comme
Externí odkaz:
http://arxiv.org/abs/2403.17830
Autor:
Lu, Chaochao, Qian, Chen, Zheng, Guodong, Fan, Hongxing, Gao, Hongzhi, Zhang, Jie, Shao, Jing, Deng, Jingyi, Fu, Jinlan, Huang, Kexin, Li, Kunchang, Li, Lijun, Wang, Limin, Sheng, Lu, Chen, Meiqi, Zhang, Ming, Ren, Qibing, Chen, Sirui, Gui, Tao, Ouyang, Wanli, Wang, Yali, Teng, Yan, Wang, Yaru, Wang, Yi, He, Yinan, Wang, Yingchun, Wang, Yixu, Zhang, Yongting, Qiao, Yu, Shen, Yujiong, Mou, Yurong, Chen, Yuxi, Zhang, Zaibin, Shi, Zhelun, Yin, Zhenfei, Wang, Zhipin
Multi-modal Large Language Models (MLLMs) have shown impressive abilities in generating reasonable responses with respect to multi-modal contents. However, there is still a wide gap between the performance of recent MLLM-based applications and the ex
Externí odkaz:
http://arxiv.org/abs/2401.15071
Multimodal Large Language Models (MLLMs) have shown impressive abilities in interacting with visual content with myriad potential downstream tasks. However, even though a list of benchmarks has been proposed, the capabilities and limitations of MLLMs
Externí odkaz:
http://arxiv.org/abs/2311.02692
Akademický článek
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Publikováno v:
Advanced Synthesis & Catalysis; Sep2019, Vol. 361 Issue 18, p4278-4285, 8p