Zobrazeno 1 - 10
of 21 729
pro vyhledávání: '"An, Ruifeng"'
Autor:
Li, Ruifeng, Liu, Wei, Zhou, Xiangxin, Li, Mingqian, Zhang, Qiang, Chen, Hongyang, Lin, Xuemin
In the drug discovery process, the low success rate of drug candidate screening often leads to insufficient labeled data, causing the few-shot learning problem in molecular property prediction. Existing methods for few-shot molecular property predict
Externí odkaz:
http://arxiv.org/abs/2410.20711
In multi-task learning, we often encounter the case when the presence of labels across samples exhibits irregular patterns: samples can be fully labeled, partially labeled or unlabeled. Taking drug analysis as an example, multiple toxicity properties
Externí odkaz:
http://arxiv.org/abs/2410.14380
When axionic dark matter interacts with a static magnetic field, it can convert into photons with energy near the axion's mass. Classical analysis shows that incorporating a resonant cavity significantly enhances this conversion rate, forming the bas
Externí odkaz:
http://arxiv.org/abs/2410.12634
Transformers have been the cornerstone of current Large Language Models (LLMs); however, its linear growth in overhead during inference with respect to sequence length poses challenges for modeling long sequences. In this context, Mamba has gradually
Externí odkaz:
http://arxiv.org/abs/2410.03810
Idioms represent a ubiquitous vehicle for conveying sentiments in the realm of everyday discourse, rendering the nuanced analysis of idiom sentiment crucial for a comprehensive understanding of emotional expression within real-world texts. Neverthele
Externí odkaz:
http://arxiv.org/abs/2409.17588
High-speed train (HST) has garnered significant attention from both academia and industry due to the rapid development of railways worldwide. Millimeter wave (mmWave) communication, known for its large bandwidth is an effective way to address perform
Externí odkaz:
http://arxiv.org/abs/2409.06946
Mixed Integer Programming (MIP) has been extensively applied in areas requiring mathematical solvers to address complex instances within tight time constraints. However, as the problem scale increases, the complexity of model formulation and finding
Externí odkaz:
http://arxiv.org/abs/2409.04464
The success of Large Language Models (LLMs) relies heavily on the huge amount of pre-training data learned in the pre-training phase. The opacity of the pre-training process and the training data causes the results of many benchmark tests to become u
Externí odkaz:
http://arxiv.org/abs/2409.01790
Autor:
Yao, Mingyuan, Huo, Yukang, Tian, Qingbin, Zhao, Jiayin, Liu, Xiao, Wang, Ruifeng, Xue, Lin, Wang, Haihua
Early detection of abnormal fish behavior caused by disease or hunger can be achieved through fish tracking using deep learning techniques, which holds significant value for industrial aquaculture. However, underwater reflections and some reasons wit
Externí odkaz:
http://arxiv.org/abs/2409.01148
Over the past few years, the YOLO series of models has emerged as one of the dominant methodologies in the realm of object detection. Many studies have advanced these baseline models by modifying their architectures, enhancing data quality, and devel
Externí odkaz:
http://arxiv.org/abs/2408.16313