Zobrazeno 1 - 10
of 11 243
pro vyhledávání: '"JIA, Jun"'
Autor:
Chen, Jinhui, Guo, Feng-Kun, Ma, Yu-Gang, Shen, Cheng-Ping, Shou, Qiye, Wang, Qian, Wu, Jia-Jun, Zou, Bing-Song
Exotic hadrons beyond the conventional quark model have been discovered in the past two decades. Investigations of these states can lead to deep understanding of nonperturbative dynamics of the strong interaction. In this concise review, we focus on
Externí odkaz:
http://arxiv.org/abs/2411.18257
Generative models such as diffusion models have achieved remarkable success in state-of-the-art image and text tasks. Recently, score-based diffusion models have extended their success beyond image generation, showing competitive performance with dis
Externí odkaz:
http://arxiv.org/abs/2411.17236
Autor:
Zhang, Zhichao, Sun, Wei, Li, Xinyue, Li, Yunhao, Ge, Qihang, Jia, Jun, Zhang, Zicheng, Ji, Zhongpeng, Sun, Fengyu, Jui, Shangling, Min, Xiongkuo, Zhai, Guangtao
AI-driven video generation techniques have made significant progress in recent years. However, AI-generated videos (AGVs) involving human activities often exhibit substantial visual and semantic distortions, hindering the practical application of vid
Externí odkaz:
http://arxiv.org/abs/2411.16619
Autor:
Zhou, Yingjie, Zhang, Zicheng, Cao, Jiezhang, Jia, Jun, Jiang, Yanwei, Wen, Farong, Liu, Xiaohong, Min, Xiongkuo, Zhai, Guangtao
Artificial Intelligence (AI) has demonstrated significant capabilities in various fields, and in areas such as human-computer interaction (HCI), embodied intelligence, and the design and animation of virtual digital humans, both practitioners and use
Externí odkaz:
http://arxiv.org/abs/2411.11235
Autor:
Szymanski, Annalisa, Ziems, Noah, Eicher-Miller, Heather A., Li, Toby Jia-Jun, Jiang, Meng, Metoyer, Ronald A.
The potential of using Large Language Models (LLMs) themselves to evaluate LLM outputs offers a promising method for assessing model performance across various contexts. Previous research indicates that LLM-as-a-judge exhibits a strong correlation wi
Externí odkaz:
http://arxiv.org/abs/2410.20266
Text documents with numerical values involved are widely used in various applications such as scientific research, economy, public health and journalism. However, it is difficult for readers to quickly interpret such data-involved texts and gain deep
Externí odkaz:
http://arxiv.org/abs/2410.14331
The rise of end-user applications powered by large language models (LLMs), including both conversational interfaces and add-ons to existing graphical user interfaces (GUIs), introduces new privacy challenges. However, many users remain unaware of the
Externí odkaz:
http://arxiv.org/abs/2410.13387
Autor:
Ma, Shang, Chen, Chaoran, Yang, Shao, Hou, Shifu, Li, Toby Jia-Jun, Xiao, Xusheng, Xie, Tao, Ye, Yanfang
In Android apps, their developers frequently place app promotion ads, namely advertisements to promote other apps. Unfortunately, the inadequate vetting of ad content allows malicious developers to exploit app promotion ads as a new distribution chan
Externí odkaz:
http://arxiv.org/abs/2410.07588
Autor:
Chen, Chaoran, Li, Leyang, Cao, Luke, Ye, Yanfang, Li, Tianshi, Yao, Yaxing, Li, Toby Jia-jun
Personalized recommendation systems tailor content based on user attributes, which are either provided or inferred from private data. Research suggests that users often hypothesize about reasons behind contents they encounter (e.g., "I see this jewel
Externí odkaz:
http://arxiv.org/abs/2410.04917
Autor:
Szymanski, Annalisa, Gebreegziabher, Simret Araya, Anuyah, Oghenemaro, Metoyer, Ronald A., Li, Toby Jia-Jun
Large Language Models (LLMs) are increasingly utilized for domain-specific tasks, yet integrating domain expertise into evaluating their outputs remains challenging. A common approach to evaluating LLMs is to use metrics, or criteria, which are asser
Externí odkaz:
http://arxiv.org/abs/2410.02054