AI RESEARCH
Reliable Modeling of Distribution Shifts via Displacement-Reshaped Optimal Transport
arXiv CS.AI
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ArXi:2605.04965v1 Announce Type: cross Optimal transport (OT) is a central framework for modeling distribution shifts. Because OT compares distributions directly in input space, a well-designed ground metric between observations is essential to ensure that the optimizer does not violate the true geometry of change. We propose Displacement-Reshaped Optimal Transport (ReshapeOT), a method that reshapes the ground metric by integrating observed sample displacements as an additional source of knowledge.