#generative modeling

New research reveals that generalization in flow matching models emerges from the neural network's approximation of velocity fields during early trajectories, challenging the belief that stochasticity drives this process.

Meta AI released Adjoint Sampling, a new scalable algorithm that trains generative models using only scalar reward signals, bypassing the need for large datasets and enabling advances in molecular modeling.