Zobrazeno 1 - 10
of 113
pro vyhledávání: '"ZHAO Sirui"'
Autor:
Yin, Shukang, Fu, Chaoyou, Zhao, Sirui, Shen, Yunhang, Ge, Chunjiang, Yang, Yan, Long, Zuwei, Dai, Yuhan, Xu, Tong, Sun, Xing, He, Ran, Shan, Caifeng, Chen, Enhong
The success of Multimodal Large Language Models (MLLMs) in the image domain has garnered wide attention from the research community. Drawing on previous successful experiences, researchers have recently explored extending the success to the video und
Externí odkaz:
http://arxiv.org/abs/2411.19951
Autor:
Fu, Chaoyou, Zhang, Yi-Fan, Yin, Shukang, Li, Bo, Fang, Xinyu, Zhao, Sirui, Duan, Haodong, Sun, Xing, Liu, Ziwei, Wang, Liang, Shan, Caifeng, He, Ran
As a prominent direction of Artificial General Intelligence (AGI), Multimodal Large Language Models (MLLMs) have garnered increased attention from both industry and academia. Building upon pre-trained LLMs, this family of models further develops mult
Externí odkaz:
http://arxiv.org/abs/2411.15296
Autor:
Shen, Tingjia, Wang, Hao, Zhang, Jiaqing, Zhao, Sirui, Li, Liangyue, Chen, Zulong, Lian, Defu, Chen, Enhong
Cross-Domain Sequential Recommendation (CDSR) aims to mine and transfer users' sequential preferences across different domains to alleviate the long-standing cold-start issue. Traditional CDSR models capture collaborative information through user and
Externí odkaz:
http://arxiv.org/abs/2406.03085
Autor:
Fu, Chaoyou, Dai, Yuhan, Luo, Yongdong, Li, Lei, Ren, Shuhuai, Zhang, Renrui, Wang, Zihan, Zhou, Chenyu, Shen, Yunhang, Zhang, Mengdan, Chen, Peixian, Li, Yanwei, Lin, Shaohui, Zhao, Sirui, Li, Ke, Xu, Tong, Zheng, Xiawu, Chen, Enhong, Ji, Rongrong, Sun, Xing
In the quest for artificial general intelligence, Multi-modal Large Language Models (MLLMs) have emerged as a focal point in recent advancements. However, the predominant focus remains on developing their capabilities in static image understanding. T
Externí odkaz:
http://arxiv.org/abs/2405.21075
Autor:
Yin, Mingjia, Wang, Hao, Guo, Wei, Liu, Yong, Zhang, Suojuan, Zhao, Sirui, Lian, Defu, Chen, Enhong
The sequential recommender (SR) system is a crucial component of modern recommender systems, as it aims to capture the evolving preferences of users. Significant efforts have been made to enhance the capabilities of SR systems. These methods typicall
Externí odkaz:
http://arxiv.org/abs/2405.17795
Autor:
Yin, Mingjia, Wang, Hao, Guo, Wei, Liu, Yong, Li, Zhi, Zhao, Sirui, Wang, Zhen, Lian, Defu, Chen, Enhong
Cross-domain sequential recommendation (CDSR) aims to uncover and transfer users' sequential preferences across multiple recommendation domains. While significant endeavors have been made, they primarily concentrated on developing advanced transfer m
Externí odkaz:
http://arxiv.org/abs/2405.12473
Autor:
Fu, Chaoyou, Zhang, Renrui, Wang, Zihan, Huang, Yubo, Zhang, Zhengye, Qiu, Longtian, Ye, Gaoxiang, Shen, Yunhang, Zhang, Mengdan, Chen, Peixian, Zhao, Sirui, Lin, Shaohui, Jiang, Deqiang, Yin, Di, Gao, Peng, Li, Ke, Li, Hongsheng, Sun, Xing
The surge of interest towards Multi-modal Large Language Models (MLLMs), e.g., GPT-4V(ision) from OpenAI, has marked a significant trend in both academia and industry. They endow Large Language Models (LLMs) with powerful capabilities in visual under
Externí odkaz:
http://arxiv.org/abs/2312.12436
Autor:
Yin, Mingjia, Wang, Hao, Xu, Xiang, Wu, Likang, Zhao, Sirui, Guo, Wei, Liu, Yong, Tang, Ruiming, Lian, Defu, Chen, Enhong
The sequential recommendation system has been widely studied for its promising effectiveness in capturing dynamic preferences buried in users' sequential behaviors. Despite the considerable achievements, existing methods usually focus on intra-sequen
Externí odkaz:
http://arxiv.org/abs/2311.02816
Autor:
Yin, Shukang, Fu, Chaoyou, Zhao, Sirui, Xu, Tong, Wang, Hao, Sui, Dianbo, Shen, Yunhang, Li, Ke, Sun, Xing, Chen, Enhong
Publikováno v:
SCIENCE CHINA Information Sciences, 2024
Hallucination is a big shadow hanging over the rapidly evolving Multimodal Large Language Models (MLLMs), referring to the phenomenon that the generated text is inconsistent with the image content. In order to mitigate hallucinations, existing studie
Externí odkaz:
http://arxiv.org/abs/2310.16045
Affordance-centric Question-driven Task Completion (AQTC) for Egocentric Assistant introduces a groundbreaking scenario. In this scenario, through learning instructional videos, AI assistants provide users with step-by-step guidance on operating devi
Externí odkaz:
http://arxiv.org/abs/2306.14412