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cs.AI2026
FlexUMM: Flexible Representation Learning for Unified Multimodal Models
Yinyi Luo, Haoyue Bai, Yi Ge +3
Unified multimodal models (UMMs) can integrate understanding and generation within a single backbone. However, it is commonly known that these two capabilities can cause conflictin…
cs.LG2026
The Physics Is the Network: Fast, Training-Free Neural Emulation
Luka Todorovic, Kaushal Gianchandani, Sai Ravela
Neural emulation need not require learning a substitute for known physics. We investigate PolyNets that couple a continuous-time neural representation of polynomial dynamics with a…