Signal from Structure: Exploiting Submodular Upper Bounds in Generative Flow Networks
arXiv:2601.21061v2 Announce Type: replace-cross
Abstract: Generative Flow Networks (GFlowNets; GFNs) are a class of generative models that learn to sample compositional objects proportionally to their a priori unknown value, their reward. We focus on …