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cs.LG2026
Partial GFlowNet: Accelerating Convergence in Large State Spaces via Strategic Partitioning
Xuan Yu, Xu Wang, Rui Zhu +2
Generative Flow Networks (GFlowNets) have shown promising potential to generate high-scoring candidates with probability proportional to their rewards. As existing GFlowNets freely…
cs.LG2026
Exploring Multiple High-Scoring Subspaces in Generative Flow Networks
Xuan Yu, Xu Wang, Rui Zhu +2
As a probabilistic sampling framework, Generative Flow Networks (GFlowNets) show strong potential for constructing complex combinatorial objects through the sequential composition…
cs.LG2026
Planning-Augmented Sampling with Early Guidance for High-Reward Discovery
Rui Zhu, Yudong Zhang, Xuan Yu +3
Generative Flow Networks (GFlowNets) enable structured generation with inherent diversity, but existing sampling strategies often rely on weak guided exploration, slowing early dis…