Data Science Wire

DCS: A Unified Conditional Sensitivity Framework for Cross-Modal Copyright Infringement Detection

arXiv cs.LG5d4 min read

arXiv:2607.22035v1 Announce Type: new Abstract: Currently, most foundation models can reproduce or strongly depend on copyrighted training content, but output similarity alone is insufficient for infringement detection, because similar outputs may also arise from public-domain concepts, common stylistic conventions, or ordinary statistical generalization. In this paper, we develops a unified post-hoc detection framework that treats copyright infringement evidence as a counterfactual conditional distribution shift: a protected target is suspicious when the model's behavior under aligned conditi

Read the full story at arXiv cs.LG

More in Governance / Quality