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pro vyhledávání: '"Tao, Quanjin"'
Recently, large language models (LLMs) have demonstrated superior capabilities in understanding and zero-shot learning on textual data, promising significant advances for many text-related domains. In the graph domain, various real-world scenarios al
Externí odkaz:
http://arxiv.org/abs/2402.12984
Autor:
Huang, Xuanwen, Han, Kaiqiao, Bao, Dezheng, Tao, Quanjin, Zhang, Zhisheng, Yang, Yang, Zhu, Qi
Text-attributed Graphs (TAGs) are commonly found in the real world, such as social networks and citation networks, and consist of nodes represented by textual descriptions. Currently, mainstream machine learning methods on TAGs involve a two-stage mo
Externí odkaz:
http://arxiv.org/abs/2309.02848
Multimodal pre-training breaks down the modality barriers and allows the individual modalities to be mutually augmented with information, resulting in significant advances in representation learning. However, graph modality, as a very general and imp
Externí odkaz:
http://arxiv.org/abs/2210.09946
Autor:
Liu, Zongtao, Dong, Wei, Wang, Chaoliang, Shen, Haoqingzi, Sun, Gang, jiang, Qun, Tao, Quanjin, Yang, Yang
Publikováno v:
In AI Open 2024 5:46-54
Publikováno v:
In AI Open 2023 4:91-97