AI RESEARCH
Some Robustness Properties of Label Cleaning
arXiv CS.LG
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ArXi:2509.11379v3 Announce Type: replace-cross We nstrate that learning procedures that rely on aggregated labels, e.g., label information distilled from noisy responses, enjoy robustness properties impossible without data cleaning. This robustness appears in several ways.