arXiv cs.AI
· Papers
Omni-modal decomposition autoencoders learn full-stack wearable disentangled representations
arXiv:2608.07385v1 Announce Type: cross Abstract: Learning disentangled representations is a key requirement for developing versatile, general-purpose, and sustainable models in multi-modal wearable computing. However, existing approaches do not operate as full-stack wearable processors, i.e., they do not simultaneousl