200 citations · 200 across the 4 of their papers we have counts for
4 papers
: Sparsifying Large Language Models via Dual Taylor Expansion and Attention Distribution Awareness
Lang Xiong, Ning Liu, Ao Ren +6
Large language models (LLMs) face significant deployment challenges due to their massive computational demands. % While pruning offers a promising compression solution, existing me…
Trustworthy Self-Attention: Enabling the Network to Focus Only on the Most Relevant References
Yu Jing, Tan Yujuan, Ren Ao +1
The prediction of optical flow for occluded points is still a difficult problem that has not yet been solved. Recent methods use self-attention to find relevant non-occluded points…
YOIO: You Only Iterate Once by mining and fusing multiple necessary global information in the optical flow estimation
Yu Jing, Tan Yujuan, Ren Ao +1
Occlusions pose a significant challenge to optical flow algorithms that even rely on global evidences. We consider an occluded point to be one that is imaged in the reference frame…
Astraea: Self-balancing Federated Learning for Improving Classification Accuracy of Mobile Deep Learning Applications
Moming Duan, Duo Liu, Xianzhang Chen +4
Federated learning (FL) is a distributed deep learning method which enables multiple participants, such as mobile phones and IoT devices, to contribute a neural network model while…