Kuaishou Tech
Apr 25, 2023 · Artificial Intelligence
DCCL: A Contrastive Learning Framework for Causal Representation Decoupling in Recommendation Systems
The paper introduces DCCL, a model‑agnostic contrastive learning framework that decouples user interest and conformity representations to address popularity bias and out‑of‑distribution challenges in recommendation systems, demonstrating significant offline and online performance gains on real‑world datasets.
OOD robustnessRecommendation systemscausal inference
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