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of 376
pro vyhledávání: '"Fu, Xianghua"'
Intent is a significant latent factor influencing user-item interaction sequences. Prevalent sequence recommendation models that utilize contrastive learning predominantly rely on single-intent representations to direct the training process. However,
Externí odkaz:
http://arxiv.org/abs/2409.08733
Autor:
Niu, Fuqiang, Cheng, Zebang, Fu, Xianghua, Peng, Xiaojiang, Dai, Genan, Chen, Yin, Huang, Hu, Zhang, Bowen
Stance detection, which aims to identify public opinion towards specific targets using social media data, is an important yet challenging task. With the proliferation of diverse multimodal social media content including text, and images multimodal st
Externí odkaz:
http://arxiv.org/abs/2409.00597
Autor:
Ye, Chuyang, Wei, Dongyan, Liu, Zhendong, Pang, Yuanyi, Lin, Yixi, Liao, Jiarong, Jiang, Qinting, Fu, Xianghua, Li, Qing, Jiang, Jingyan
Test-time adaptation (TTA) effectively addresses distribution shifts between training and testing data by adjusting models on test samples, which is crucial for improving model inference in real-world applications. However, traditional TTA methods ty
Externí odkaz:
http://arxiv.org/abs/2408.08056
Recent research in the field of multimodal machine translation (MMT) has indicated that the visual modality is either dispensable or offers only marginal advantages. However, most of these conclusions are drawn from the analysis of experimental resul
Externí odkaz:
http://arxiv.org/abs/2404.06107
Autor:
Zhang, Bowen, Fu, Xianghua, Ding, Daijun, Huang, Hu, Dai, Genan, Yin, Nan, Li, Yangyang, Jing, Liwen
Stance detection predicts attitudes towards targets in texts and has gained attention with the rise of social media. Traditional approaches include conventional machine learning, early deep neural networks, and pre-trained fine-tuning models. However
Externí odkaz:
http://arxiv.org/abs/2304.03087
Recently, numbers of works shows that the performance of neural machine translation (NMT) can be improved to a certain extent with using visual information. However, most of these conclusions are drawn from the analysis of experimental results based
Externí odkaz:
http://arxiv.org/abs/2208.00767
Publikováno v:
In Neurocomputing 28 November 2024 607
Autor:
Ding, Daijun1 (AUTHOR) dingdaijun2021@email.szu.edu.cn, Fu, Xianghua2 (AUTHOR) fuxianghua@sztu.edu.cn, Peng, Xiaojiang2 (AUTHOR) pengxiaojiang@sztu.edu.cn, Fan, Xiaomao2 (AUTHOR) fanxiaoma@sztu.edu.cn, Huang, Hu3 (AUTHOR) h.huang@pku.edu.cn, Zhang, Bowen2 (AUTHOR) h.huang@pku.edu.cn
Publikováno v:
Mathematics (2227-7390). Feb2024, Vol. 12 Issue 4, p568. 16p.
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