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cs.LG2026
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…
cs.LG2026
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…
cs.LG2020★ 1 cited
Learning Principle of Least Action with Reinforcement Learning
Zehao Jin, Joshua Yao-Yu Lin, Siao-Fong Li
Nature provides a way to understand physics with reinforcement learning since nature favors the economical way for an object to propagate. In the case of classical mechanics, natur…