Zobrazeno 51 - 60
of 46 289
pro vyhledávání: '"Zhang, Wen"'
Knowledge graph embedding (KGE) aims to map entities and relations of a knowledge graph (KG) into a low-dimensional and dense vector space via contrasting the positive and negative triples. In the training process of KGEs, negative sampling is essent
Externí odkaz:
http://arxiv.org/abs/2310.09781
Large language model (LLM) based knowledge graph completion (KGC) aims to predict the missing triples in the KGs with LLMs. However, research about LLM-based KGC fails to sufficiently harness LLMs' inference proficiencies, overlooking critical struct
Externí odkaz:
http://arxiv.org/abs/2310.06671
Autor:
Zhang, Wen-Long, Li, Xiu-Juan, Yang, Yu-Peng, Yi, Shuang-Xi, Li, Cheng-Kui, Tang, Qing-Wen, Qin, Ying, Wang, Fa-Yin
Publikováno v:
RAA, 2023, 23:115013
As one class of the most important objects in the universe, magnetars can produce a lot of different frequency bursts including X-ray bursts. In \cite{2022ApJS..260...24C}, 75 X-ray bursts produced by magnetar SGR J1935+2154 during an active period i
Externí odkaz:
http://arxiv.org/abs/2310.06299
Identifying intrinsic noncollinear magnetic order in monolayer van der Waals (vdW) crystals is highly desirable for understanding the delicate magnetic interactions at reduced spatial constraints and miniaturized spintronic applications, but remains
Externí odkaz:
http://arxiv.org/abs/2309.16526
A full-quantum approach is used to study quantum nonlinear properties of a compound Michelson-Sagnac interferometer optomechanical system. The effective Hamiltonian shows that both dissipative and dispersive couplings possess imaginary- and real-Kerr
Externí odkaz:
http://arxiv.org/abs/2309.03719
Knowledge Graph Embedding (KGE) has proven to be an effective approach to solving the Knowledge Graph Completion (KGC) task. Relational patterns which refer to relations with specific semantics exhibiting graph patterns are an important factor in the
Externí odkaz:
http://arxiv.org/abs/2308.07889
Recent years have seen significant advancements in multi-modal knowledge graph completion (MMKGC). MMKGC enhances knowledge graph completion (KGC) by integrating multi-modal entity information, thereby facilitating the discovery of unobserved triples
Externí odkaz:
http://arxiv.org/abs/2308.06696
Autor:
Zhang, Wen, Xia, Bohang, Derks, Daantje, Pletzer, Jan Luca, Breevaart, Kimberley, Zhang, Xichao
Publikováno v:
Journal of Managerial Psychology, 2024, Vol. 39, Issue 5, pp. 539-554.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/JMP-06-2022-0310
Autor:
Chen, Zhuo, Guo, Lingbing, Fang, Yin, Zhang, Yichi, Chen, Jiaoyan, Pan, Jeff Z., Li, Yangning, Chen, Huajun, Zhang, Wen
As a crucial extension of entity alignment (EA), multi-modal entity alignment (MMEA) aims to identify identical entities across disparate knowledge graphs (KGs) by exploiting associated visual information. However, existing MMEA approaches primarily
Externí odkaz:
http://arxiv.org/abs/2307.16210