Zobrazeno 1 - 10
of 22 093
pro vyhledávání: '"Zhou, Xiao"'
In recent years, vision-language models have made significant strides, excelling in tasks like optical character recognition and geometric problem-solving. However, several critical issues remain: 1) Proprietary models often lack transparency about t
Externí odkaz:
http://arxiv.org/abs/2409.04828
Most large language models are fine-tuned using either expensive human-annotated data or GPT-4 generated data which cannot guarantee performance in certain domains. We argue that although the web-crawled data often has formatting errors causing seman
Externí odkaz:
http://arxiv.org/abs/2408.08003
For autonomous driving in highly dynamic environments, it is anticipated to predict the future behaviors of surrounding vehicles (SVs) and make safe and effective decisions. However, modeling the inherent coupling effect between the prediction and de
Externí odkaz:
http://arxiv.org/abs/2408.03191
Autor:
Xu, Zhuo, Zhou, Xiao
The explosion of massive urban data recently has provided us with a valuable opportunity to gain deeper insights into urban regions and the daily lives of residents. Urban region representation learning emerges as a crucial realm for fulfilling this
Externí odkaz:
http://arxiv.org/abs/2407.02074
Autor:
Huang, De-Xing, Zhou, Xiao-Hu, Xie, Xiao-Liang, Liu, Shi-Qi, Wang, Shuang-Yi, Feng, Zhen-Qiu, Gui, Mei-Jiang, Li, Hao, Xiang, Tian-Yu, Yao, Bo-Xian, Hou, Zeng-Guang
Automatic vessel segmentation is paramount for developing next-generation interventional navigation systems. However, current approaches suffer from suboptimal segmentation performances due to significant challenges in intraoperative images (i.e., lo
Externí odkaz:
http://arxiv.org/abs/2406.19749
Ratings of a user to most items in recommender systems are usually missing not at random (MNAR), largely because users are free to choose which items to rate. To achieve unbiased learning of the prediction model under MNAR data, three typical solutio
Externí odkaz:
http://arxiv.org/abs/2406.17182
Autor:
Yong, Xixian, Zhou, Xiao
Predicting socioeconomic indicators within urban regions is crucial for fostering inclusivity, resilience, and sustainability in cities and human settlements. While pioneering studies have attempted to leverage multi-modal data for socioeconomic pred
Externí odkaz:
http://arxiv.org/abs/2407.09523
The Bell nonlocality and entanglement are two kinds of quantum correlations in quantum systems. Due to the recent upgrade in Beijing Spectrometer III (BESIII) experiment, it is possible to explore the nonlocality and entanglement in hyperon-antihyper
Externí odkaz:
http://arxiv.org/abs/2406.16298
When evaluating the effectiveness of a drug, a Randomized Controlled Trial (RCT) is often considered the gold standard due to its perfect randomization. While RCT assures strong internal validity, its restricted external validity poses challenges in
Externí odkaz:
http://arxiv.org/abs/2406.04107
Publication bias (PB) poses a significant threat to meta-analysis, as studies yielding notable results are more likely to be published in scientific journals. Sensitivity analysis provides a flexible method to address PB and to examine the impact of
Externí odkaz:
http://arxiv.org/abs/2406.04095