Zobrazeno 1 - 10
of 4 238
pro vyhledávání: '"Liu, XiaoLong"'
Autor:
Su, Xiaorui, Wang, Yibo, Gao, Shanghua, Liu, Xiaolong, Giunchiglia, Valentina, Clevert, Djork-Arné, Zitnik, Marinka
Biomedical knowledge is uniquely complex and structured, requiring distinct reasoning strategies compared to other scientific disciplines like physics or chemistry. Biomedical scientists do not rely on a single approach to reasoning; instead, they us
Externí odkaz:
http://arxiv.org/abs/2410.04660
Generating images with accurately represented text, especially in non-Latin languages, poses a significant challenge for diffusion models. Existing approaches, such as the integration of hint condition diagrams via auxiliary networks (e.g., ControlNe
Externí odkaz:
http://arxiv.org/abs/2409.17524
Recent advances in unsupervised representation learning often rely on knowing the number of classes to improve feature extraction and clustering. However, this assumption raises an important question: is the number of classes always necessary, and do
Externí odkaz:
http://arxiv.org/abs/2409.04867
Autor:
Regmi, Resham Babu, Bhandari, Hari, Thapa, Bishal, Hao, Yiqing, Sharma, Nileema, McKenzie, James, Chen, Xinglong, Nayak, Abhijeet, Gazzah, Mohamed El, Márkus, Bence Gábor, Forró, László, Liu, Xiaolong, Cao, Huibo, Mitchell, J. F., Mazin, I. I., Ghimire, Nirmal J.
Altermagnets (AMs) are a new class of magnetic materials that combine the beneficial spintronics properties of ferromagnets and antiferromagnets, garnering significant attention recently. Here, we have identified altermagnetism in a layered intercala
Externí odkaz:
http://arxiv.org/abs/2408.08835
Autor:
Yang, Mingdai, Liu, Zhiwei, Yang, Liangwei, Liu, Xiaolong, Wang, Chen, Peng, Hao, Yu, Philip S.
Pretraining has been widely explored to augment the adaptability of graph learning models to transfer knowledge from large datasets to a downstream task, such as link prediction or classification. However, the gap between training objectives and the
Externí odkaz:
http://arxiv.org/abs/2403.19063
In recent years, knowledge distillation methods based on contrastive learning have achieved promising results on image classification and object detection tasks. However, in this line of research, we note that less attention is paid to semantic segme
Externí odkaz:
http://arxiv.org/abs/2312.04168
Social networks have become essential for people's lives. The proliferation of web services further expands social networks at an unprecedented scale, leading to immeasurable commercial value for online platforms. Recently, the group buying (GB) busi
Externí odkaz:
http://arxiv.org/abs/2311.12136
Autor:
Liu, Xiaolong, Yang, Liangwei, Liu, Zhiwei, Li, Xiaohan, Yang, Mingdai, Wang, Chen, Yu, Philip S.
Personalized recommender systems aim to predict users' preferences for items. It has become an indispensable part of online services. Online social platforms enable users to form groups based on their common interests. The users' group participation
Externí odkaz:
http://arxiv.org/abs/2311.09577
Autor:
Yang, Mingdai, Liu, Zhiwei, Yang, Liangwei, Liu, Xiaolong, Wang, Chen, Peng, Hao, Yu, Philip S.
Although pretraining has garnered significant attention and popularity in recent years, its application in graph-based recommender systems is relatively limited. It is challenging to exploit prior knowledge by pretraining in widely used ID-dependent
Externí odkaz:
http://arxiv.org/abs/2310.13286
Autor:
Liu, Xiaolong, Yang, Liangwei, Liu, Zhiwei, Yang, Mingdai, Wang, Chen, Peng, Hao, Yu, Philip S.
The field of Recommender Systems (RecSys) has been extensively studied to enhance accuracy by leveraging users' historical interactions. Nonetheless, this persistent pursuit of accuracy frequently engenders diminished diversity, culminating in the we
Externí odkaz:
http://arxiv.org/abs/2310.13253