1 citations · 2 across the 8 of their papers we have counts for
8 papers
Do Vision Transformers Need All-to-All Attention? Global Communication Through Elastic Learned Cores
Alan Z. Song, Yinjie Chen, Mu Nan +8
Vision Transformers (ViTs) learn rich visual-semantic representations through all-to-all self-attention among patch tokens. However, this design implicitly assumes that direct pair…
NeuroFlow: Toward Unified Visual Encoding and Decoding from Neural Activity
Weijian Mai, Mu Nan, Yu Zhu +6
Visual encoding and decoding models act as gateways to understanding the neural mechanisms underlying human visual perception. Typically, visual encoding models that predict brain…
Meta-learning In-Context Enables Training-Free Cross Subject Brain Decoding
Mu Nan, Muquan Yu, Weijian Mai +12
Visual decoding from brain signals is a key challenge at the intersection of computer vision and neuroscience, requiring methods that bridge neural representations and computationa…
Compose Your Policies! Improving Diffusion-based or Flow-based Robot Policies via Test-time Distribution-level Composition
Jiahang Cao, Yize Huang, Hanzhong Guo +15
Diffusion-based models for robotic control, including vision-language-action (VLA) and vision-action (VA) policies, have demonstrated significant capabilities. Yet their advancemen…
SynBrain: Enhancing Visual-to-fMRI Synthesis via Probabilistic Representation Learning
Weijian Mai, Jiamin Wu, Yu Zhu +6
Deciphering how visual stimuli are transformed into cortical responses is a fundamental challenge in computational neuroscience. This visual-to-neural mapping is inherently a one-t…
UniMind: Unleashing the Power of LLMs for Unified Multi-Task Brain Decoding
Weiheng Lu, Zhouheng Yao, Jiamin Wu +6
Decoding human brain activity from electroencephalography (EEG) signals is a central challenge at the intersection of neuroscience and artificial intelligence, enabling diverse app…
MindAligner: Explicit Brain Functional Alignment for Cross-Subject Visual Decoding from Limited fMRI Data
Yuqin Dai, Zhouheng Yao, Chunfeng Song +7
Brain decoding aims to reconstruct visual perception of human subject from fMRI signals, which is crucial for understanding brain's perception mechanisms. Existing methods are conf…
Neuro-3D: Towards 3D Visual Decoding from EEG Signals
Zhanqiang Guo, Jiamin Wu, Yonghao Song +5
Human's perception of the visual world is shaped by the stereo processing of 3D information. Understanding how the brain perceives and processes 3D visual stimuli in the real world…