Unextractable Protocol Models: Collaborative Training and Inference without Weight Materialization

ArXi:2605.23464v1 Announce Type: new We consider a decentralized setup in which the participants collaboratively train and serve a large neural network, and where each participant only processes a subset of the model. In this setup, we explore the possibility of unmaterializable weights, where a full weight set is never available to any one participant. We