Zobrazeno 1 - 10
of 48 430
pro vyhledávání: '"Liu, Yong"'
Semi-supervised learning (SSL) has shown considerable potential in medical image segmentation, primarily leveraging consistency regularization and pseudo-labeling. However, many SSL approaches only pay attention to low-level consistency and overlook
Externí odkaz:
http://arxiv.org/abs/2406.19649
The element boron has long been central to two-dimensional superconducting materials, and numerous studies have demonstrated the presence of superconductivity in various boron-based structures. Recent work introduced a new variant: Bilayer Kagome bor
Externí odkaz:
http://arxiv.org/abs/2406.18165
Autor:
Zhu, Guanghao, Liu, Lin, Hu, Yuhao, Sun, Haixin, Liu, Fang, Du, Xiaohui, Hao, Ruqian, Liu, Juanxiu, Liu, Yong, Deng, Hao, Zhang, Jing
Micro-expressions (MEs) are subtle facial movements that occur spontaneously when people try to conceal the real emotions. Micro-expression recognition (MER) is crucial in many fields, including criminal analysis and psychotherapy. However, MER is ch
Externí odkaz:
http://arxiv.org/abs/2406.17538
Graph autoencoders (GAEs), as a kind of generative self-supervised learning approach, have shown great potential in recent years. GAEs typically rely on distance-based criteria, such as mean-square-error (MSE), to reconstruct the input graph. However
Externí odkaz:
http://arxiv.org/abs/2406.17517
Autor:
Hu, Yulan, Li, Qingyang, Ouyang, Sheng, Chen, Ge, Chen, Kaihui, Mei, Lijun, Ye, Xucheng, Zhang, Fuzheng, Liu, Yong
Reinforcement Learning from Human Feedback (RLHF) facilitates the alignment of large language models (LLMs) with human preferences, thereby enhancing the quality of responses generated. A critical component of RLHF is the reward model, which is train
Externí odkaz:
http://arxiv.org/abs/2406.16486
Benefiting from the advancements in large language models and cross-modal alignment, existing multi-modal video understanding methods have achieved prominent performance in offline scenario. However, online video streams, as one of the most common me
Externí odkaz:
http://arxiv.org/abs/2406.08085
The exploitation of piezoelectric ferromagnetism (PFM) in two-dimensional (2D) materials with large out-of-plane piezoelectric response is motivated not only by technological applications but also scientific interest. In this study, the CrONM monolay
Externí odkaz:
http://arxiv.org/abs/2406.06265
Pre-trained large language models (LLMs) based on Transformer have demonstrated striking in-context learning (ICL) abilities. With a few demonstration input-label pairs, they can predict the label for an unseen input without any parameter updates. In
Externí odkaz:
http://arxiv.org/abs/2406.03768
Autor:
Zhang, Jiangning, He, Haoyang, Gan, Zhenye, He, Qingdong, Cai, Yuxuan, Xue, Zhucun, Wang, Yabiao, Wang, Chengjie, Xie, Lei, Liu, Yong
Visual anomaly detection aims to identify anomalous regions in images through unsupervised learning paradigms, with increasing application demand and value in fields such as industrial inspection and medical lesion detection. Despite significant prog
Externí odkaz:
http://arxiv.org/abs/2406.03262
Autor:
Nie, Qiang, Fu, Weifu, Lin, Yuhuan, Li, Jialin, Zhou, Yifeng, Liu, Yong, Zhu, Lei, Wang, Chengjie
Instance-incremental learning (IIL) focuses on learning continually with data of the same classes. Compared to class-incremental learning (CIL), the IIL is seldom explored because IIL suffers less from catastrophic forgetting (CF). However, besides r
Externí odkaz:
http://arxiv.org/abs/2406.03065