Zobrazeno 1 - 10
of 190
pro vyhledávání: '"Shuang, Kai"'
Autor:
Yang, Shuang-Kai, Zhang, Wei-Min
Entanglement is the most striking but also most weird property in quantum mechanics, even though it has been confirmed by many experiments over decades through the criterion of violating Bell's inequality. However, a fundamental questions arisen from
Externí odkaz:
http://arxiv.org/abs/2403.09368
In dialogue state tracking, dialogue history is a crucial material, and its utilization varies between different models. However, no matter how the dialogue history is used, each existing model uses its own consistent dialogue history during the enti
Externí odkaz:
http://arxiv.org/abs/2205.10059
Autor:
Shi, Lei, Shuang, Kai, Geng, Shijie, Gao, Peng, Fu, Zuohui, de Melo, Gerard, Chen, Yunpeng, Su, Sen
Inspired by the success of BERT, several multimodal representation learning approaches have been proposed that jointly represent image and text. These approaches achieve superior performance by capturing high-level semantic information from large-sca
Externí odkaz:
http://arxiv.org/abs/2109.11778
The goal of dialogue state tracking (DST) is to predict the current dialogue state given all previous dialogue contexts. Existing approaches generally predict the dialogue state at every turn from scratch. However, the overwhelming majority of the sl
Externí odkaz:
http://arxiv.org/abs/2107.12578
Publikováno v:
In Information Processing and Management January 2024 61(1)
More personal consumer loan products are emerging in mobile banking APP. For ease of use, application process is always simple, which means that few application information is requested for user to fill when applying for a loan, which is not conduciv
Externí odkaz:
http://arxiv.org/abs/2008.07796
Autor:
Shi, Lei, Shuang, Kai, Geng, Shijie, Su, Peng, Jiang, Zhengkai, Gao, Peng, Fu, Zuohui, de Melo, Gerard, Su, Sen
Several multi-modality representation learning approaches such as LXMERT and ViLBERT have been proposed recently. Such approaches can achieve superior performance due to the high-level semantic information captured during large-scale multimodal pretr
Externí odkaz:
http://arxiv.org/abs/2007.13135
Multi-modality fusion technologies have greatly improved the performance of neural network-based Video Description/Caption, Visual Question Answering (VQA) and Audio Visual Scene-aware Dialog (AVSD) over the recent years. Most previous approaches onl
Externí odkaz:
http://arxiv.org/abs/2001.05840
Publikováno v:
In Information Sciences October 2023 645
The vanilla LSTM has become one of the most potential architectures in word-level language modeling, like other recurrent neural networks, overfitting is always a key barrier for its effectiveness. The existing noise-injected regularizations introduc
Externí odkaz:
http://arxiv.org/abs/1907.10885