25 citations · 70 across the 26 of their papers we have counts for
8 papers · 1 filter
Bridging the Divide: Reconsidering Softmax and Linear Attention
Dongchen Han, Yifan Pu, Zhuofan Xia +6
Widely adopted in modern Vision Transformer designs, Softmax attention can effectively capture long-range visual information; however, it incurs excessive computational cost when d…
Advancing Generalization in PINNs through Latent-Space Representations
Honghui Wang, Yifan Pu, Shiji Song +1
Physics-informed neural networks (PINNs) have made significant strides in modeling dynamical systems governed by partial differential equations (PDEs). However, their generalizatio…
Exploring contextual modeling with linear complexity for point cloud segmentation
Yong Xien Chng, Xuchong Qiu, Yizeng Han +3
Point cloud segmentation is an important topic in 3D understanding that has traditionally has been tackled using either the CNN or Transformer. Recently, Mamba has emerged as a pro…
Efficient Diffusion Transformer with Step-wise Dynamic Attention Mediators
Yifan Pu, Zhuofan Xia, Jiayi Guo +9
This paper identifies significant redundancy in the query-key interactions within self-attention mechanisms of diffusion transformer models, particularly during the early stages of…
Demystify Mamba in Vision: A Linear Attention Perspective
Dongchen Han, Ziyi Wang, Zhuofan Xia +7
Mamba is an effective state space model with linear computation complexity. It has recently shown impressive efficiency in dealing with high-resolution inputs across various vision…
2023 Low-Power Computer Vision Challenge (LPCVC) Summary
Leo Chen, Benjamin Boardley, Ping Hu +27
This article describes the 2023 IEEE Low-Power Computer Vision Challenge (LPCVC). Since 2015, LPCVC has been an international competition devoted to tackling the challenge of compu…
GRA: Detecting Oriented Objects through Group-wise Rotating and Attention
Jiangshan Wang, Yifan Pu, Yizeng Han +4
Oriented object detection, an emerging task in recent years, aims to identify and locate objects across varied orientations. This requires the detector to accurately capture the or…
PsychoGAT: A Novel Psychological Measurement Paradigm through Interactive Fiction Games with LLM Agents
Qisen Yang, Zekun Wang, Honghui Chen +6
Psychological measurement is essential for mental health, self-understanding, and personal development. Traditional methods, such as self-report scales and psychologist interviews,…