2026
On the Fragility of Data Attribution When Learning Is Distributed
ICML 2026poster
Data attribution has become a core primitive for pricing, auditing, and governing machine learning pipelines, yet current attribution methods implicitly assume that attribution value faithfully reflects participants' contributions. We show that this assumption can fail: a single participant in a sta…