6 papers across 3 sessions
This paper proposes the Multi-Task Learning with Knowledge Distillation (MTL-KD) to train a single heavy decoder model without labeled data to solve various VRP variants.
we introduce the Hybrid-Balance GFlowNet framework which uniquely integrates TB and DB in a principled and adaptive manner to acheive Local-Global Optimization.