SOURCE-LINKED INTELLIGENCE

From Feature Interaction to Feature Transport - A Unified Block for Scalable Recommendation Models

arXiv · AI, language, vision and robotics · article · Aug 31, 2026 · UTC

Unified recommendation models aim to jointly model non-sequential multi-field features and sequential user behaviors, but existing interaction-centric designs mainly focus on mixing heterogeneous tokens within each layer. We argue that scalable unified recommendation also requires controlling how intent information is carried, filtered, and preserved across stacked blocks. Inspired by flow-based representation dynamics, we introduce feature transport, a view that treats deep unified recommendation as a discrete context-conditioned representation evolution process. We propose CRAFT, a Contextua

Read original source ↗ Open in workspace

recordType

paper

region

Global