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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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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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Are we really making much progress? Revisiting, benchmarking, and refining heterogeneous graph neural networks



Qingsong Lv , Ming Ding , Qiang Liu , Yuxiang Chen , Wenzheng Feng , Siming He , Chang Zhou , Jianguo Jiang , Yuxiao Dong , Jie Tang

* KDD 2021 research track 

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M6-10T: A Sharing-Delinking Paradigm for Efficient Multi-Trillion Parameter Pretraining



Junyang Lin , An Yang , Jinze Bai , Chang Zhou , Le Jiang , Xianyan Jia , Ang Wang , Jie Zhang , Yong Li , Wei Lin , Jingren Zhou , Hongxia Yang

* 14 pages, 4 figures 

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Causal Attention for Unbiased Visual Recognition



Tan Wang , Chang Zhou , Qianru Sun , Hanwang Zhang

* Accepted by ICCV 2021 

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