15 citations · 17 across the 3 of their papers we have counts for
5 papers
Pre-Trained Models: Past, Present and Future
Xu Han, Zhengyan Zhang, Ning Ding +21
Large-scale pre-trained models (PTMs) such as BERT and GPT have recently achieved great success and become a milestone in the field of artificial intelligence (AI). Owing to sophis…
WenLan: Bridging Vision and Language by Large-Scale Multi-Modal Pre-Training
Yuqi Huo, Manli Zhang, Guangzhen Liu +32
Multi-modal pre-training models have been intensively explored to bridge vision and language in recent years. However, most of them explicitly model the cross-modal interaction bet…
Smoothed Gaussian Mixture Models for Video Classification and Recommendation
Sirjan Kafle, Aman Gupta, Xue Xia +4
Cluster-and-aggregate techniques such as Vector of Locally Aggregated Descriptors (VLAD), and their end-to-end discriminatively trained equivalents like NetVLAD have recently been…
More Industry-friendly: Federated Learning with High Efficient Design
Dingwei Li, Qinglong Chang, Lixue Pang +4
Although many achievements have been made since Google threw out the paradigm of federated learning (FL), there still exists much room for researchers to optimize its efficiency. I…
How does Weight Correlation Affect the Generalisation Ability of Deep Neural Networks
Gaojie Jin, Xinping Yi, Liang Zhang +3
This paper studies the novel concept of weight correlation in deep neural networks and discusses its impact on the networks' generalisation ability. For fully-connected layers, the…