most citedEfficientViT: Memory Efficient Vision Transformer with Cascaded Group Attention

37 citations · 48 across the 11 of their papers we have counts for

collaborators

11 papers

cs.CL2023

End-to-End Word-Level Pronunciation Assessment with MASK Pre-training

Yukang Liang, Kaitao Song, Shaoguang Mao +6

Pronunciation assessment is a major challenge in the computer-aided pronunciation training system, especially at the word (phoneme)-level. To obtain word (phoneme)-level scores, cu…

cs.CL2023

Accurate and Structured Pruning for Efficient Automatic Speech Recognition

Huiqiang Jiang, Li Lyna Zhang, Yuang Li +7

Automatic Speech Recognition (ASR) has seen remarkable advancements with deep neural networks, such as Transformer and Conformer. However, these models typically have large model s…

cs.CL20231 cited

An AMR-based Link Prediction Approach for Document-level Event Argument Extraction

Yuqing Yang, Qipeng Guo, Xiangkun Hu +3

Recent works have introduced Abstract Meaning Representation (AMR) for Document-level Event Argument Extraction (Doc-level EAE), since AMR provides a useful interpretation of compl…

cs.CV202337 cited

EfficientViT: Memory Efficient Vision Transformer with Cascaded Group Attention

Xinyu Liu, Houwen Peng, Ningxin Zheng +3

Vision transformers have shown great success due to their high model capabilities. However, their remarkable performance is accompanied by heavy computation costs, which makes them…

cs.CV2023

Learned Focused Plenoptic Image Compression with Microimage Preprocessing and Global Attention

Kedeng Tong, Xin Jin, Yuqing Yang +3

Focused plenoptic cameras can record spatial and angular information of the light field (LF) simultaneously with higher spatial resolution relative to traditional plenoptic cameras…

cs.CV2023

ElasticViT: Conflict-aware Supernet Training for Deploying Fast Vision Transformer on Diverse Mobile Devices

Chen Tang, Li Lyna Zhang, Huiqiang Jiang +6

Neural Architecture Search (NAS) has shown promising performance in the automatic design of vision transformers (ViT) exceeding 1G FLOPs. However, designing lightweight and low-lat…