UniCon: a unified context-centric modeling paradigm for industrial CTR prediction
_reachsumit · x · 2026-09-04
UniCon proposes a unified context-centric architecture for CTR prediction that treats each display list as the basic modeling unit, organizing history and prediction targets as homogeneous context units.
Intra-context attention captures local coupling among items within a context, while inter-context attention models the dynamics of decision states across contexts. The authors argue existing token-level unified modeling stems from legacy feature engineering and misaligns with the user's decision process, limiting scaling efficiency in context-rich settings like e-commerce shelves and waterfall feeds.
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