DeconDTN-Toolkit: A Library for Evaluation and Enhancement of Robustness to Provenance Shift

ArXi:2605.11237v1 Announce Type: new Despite the burgeoning body of work on distribution shifts, provenance shift-where the relationship between data source and label changes at deployment-remains poorly understood and under-addressed. In this paper, we establish a formal connection between provenance shift, counterfactual invariance, and invariant learning to derive a learning objective for robustness. We then