AI RESEARCH
On the Fragility of Data Attribution When Learning Is Distributed
arXiv CS.AI
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ArXi:2605.15520v1 Announce Type: cross Data attribution has become an important component of pricing, auditing, and governance in machine learning pipelines, yet most attribution methods implicitly assume that attribution values faithfully reflect participants' contributions. We show that this assumption can fail: a single participant in a standard distributed