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pro vyhledávání: '"Yao, Barry"'
Autor:
Gong, Xuan, Li, Shanglin, Bao, Yuxiang, Yao, Barry, Huang, Yawen, Wu, Ziyan, Zhang, Baochang, Zheng, Yefeng, Doermann, David
Federated learning (FL) is a machine learning paradigm in which distributed local nodes collaboratively train a central model without sharing individually held private data. Existing FL methods either iteratively share local model parameters or deplo
Externí odkaz:
http://arxiv.org/abs/2312.14478
Autor:
Yao, Barry Menglong, Chen, Yu, Wang, Qifan, Wang, Sijia, Liu, Minqian, Xu, Zhiyang, Yu, Licheng, Huang, Lifu
We propose attribute-aware multimodal entity linking, where the input is a mention described with a text and image, and the goal is to predict the corresponding target entity from a multimodal knowledge base (KB) where each entity is also described w
Externí odkaz:
http://arxiv.org/abs/2305.14725
Publikováno v:
Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR '23), July 23--27, 2023, Taipei, Taiwan
We propose end-to-end multimodal fact-checking and explanation generation, where the input is a claim and a large collection of web sources, including articles, images, videos, and tweets, and the goal is to assess the truthfulness of the claim by re
Externí odkaz:
http://arxiv.org/abs/2205.12487