6 citations · 15 across the 18 of their papers we have counts for
4 papers · 1 filter
GhostRNN: Reducing State Redundancy in RNN with Cheap Operations
Hang Zhou, Xiaoxu Zheng, Yunhe Wang +3
Recurrent neural network (RNNs) that are capable of modeling long-distance dependencies are widely used in various speech tasks, eg., keyword spotting (KWS) and speech enhancement…
Vista3D: Unravel the 3D Darkside of a Single Image
Qiuhong Shen, Xingyi Yang, Michael Bi Mi +1
We embark on the age-old quest: unveiling the hidden dimensions of objects from mere glimpses of their visible parts. To address this, we present Vista3D, a framework that realizes…
Isomorphic Pruning for Vision Models
Gongfan Fang, Xinyin Ma, Michael Bi Mi +1
Structured pruning reduces the computational overhead of deep neural networks by removing redundant sub-structures. However, assessing the relative importance of different sub-stru…
Learning-to-Cache: Accelerating Diffusion Transformer via Layer Caching
Xinyin Ma, Gongfan Fang, Michael Bi Mi +1
Diffusion Transformers have recently demonstrated unprecedented generative capabilities for various tasks. The encouraging results, however, come with the cost of slow inference, s…