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Knowledge Distillation of Transformer-based Language Models Revisited



Chengqiang Lu , Jianwei Zhang , Yunfei Chu , Zhengyu Chen , Jingren Zhou , Fei Wu , Haiqing Chen , Hongxia Yang


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Instance-wise Prompt Tuning for Pretrained Language Models



Yuezihan Jiang , Hao Yang , Junyang Lin , Hanyu Zhao , An Yang , Chang Zhou , Hongxia Yang , Zhi Yang , Bin Cui


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GraphMAE: Self-Supervised Masked Graph Autoencoders



Zhenyu Hou , Xiao Liu , Yukuo Cen , Yuxiao Dong , Hongxia Yang , Chunjie Wang , Jie Tang

* 11 pages; Accepted to KDD'22 

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M6-Fashion: High-Fidelity Multi-modal Image Generation and Editing



Zhikang Li , Huiling Zhou , Shuai Bai , Peike Li , Chang Zhou , Hongxia Yang

* arXiv admin note: text overlap with arXiv:2105.14211 

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M6-Rec: Generative Pretrained Language Models are Open-Ended Recommender Systems



Zeyu Cui , Jianxin Ma , Chang Zhou , Jingren Zhou , Hongxia Yang

* 10 pages, 8 figures, proudly rejected by KDD 2022 

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In-N-Out Generative Learning for Dense Unsupervised Video Segmentation



Xiao Pan , Peike Li , Zongxin Yang , Huiling Zhou , Chang Zhou , Hongxia Yang , Jingren Zhou , Yi Yang


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Modality Competition: What Makes Joint Training of Multi-modal Network Fail in Deep Learning? (Provably)



Yu Huang , Junyang Lin , Chang Zhou , Hongxia Yang , Longbo Huang

* 41 pages, 2 figures 

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Unifying Architectures, Tasks, and Modalities Through a Simple Sequence-to-Sequence Learning Framework



Peng Wang , An Yang , Rui Men , Junyang Lin , Shuai Bai , Zhikang Li , Jianxin Ma , Chang Zhou , Jingren Zhou , Hongxia Yang

* 23 pages, 11 figures 

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Deep Unified Representation for Heterogeneous Recommendation



Chengqiang Lu , Mingyang Yin , Shuheng Shen , Luo Ji , Qi Liu , Hongxia Yang

* 12 pages, 4 figures, accepted by the ACM Web Conference 2022 (WWW '22) 

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