5 papers
Whole-Brain Connectomic Graph Model Enables Whole-Body Locomotion Control in Fruit Fly
Zehao Jin, Yaoye Zhu, Chen Zhang +1
Animals perform coordinated whole-body movements under the control of neural systems shaped by brain-wide connectivity. The mapping of the whole-brain neural connections, or the co…
Decompose Sparsely Where You Should, Absorb Densely Where You Should No
Ruixuan Deng, Zehao Jin, Zekun Wang +1
Sparse autoencoders (SAEs) are typically trained to reconstruct the \textbf{entire} residual stream through a sparse dictionary, implicitly assuming that all activation content is…
How Far Are VLMs from Privacy Awareness in the Physical World? An Empirical Study
Junran Wang, Xinjie Shen, Zehao Jin +1
As Vision-Language Models (VLMs) are increasingly deployed as autonomous cognitive cores for embodied assistants, evaluating their privacy awareness in physical environments become…
Beyond Steering Vector: Flow-based Activation Steering for Inference-Time Intervention
Zehao Jin, Ruixuan Deng, Junran Wang +2
Activation steering has emerged as a promising alternative for controlling language-model behavior at inference time by modifying intermediate representations while keeping model p…
Stochastic Attention: Connectome-Inspired Randomized Routing for Expressive Linear-Time Attention
Zehao Jin, Yanan Sui
The whole-brain connectome of a fruit fly comprises over 130K neurons connected with a probability of merely 0.02%, yet achieves an average shortest path of only 4.4 hops. Despite…