Global-Context Attention Fusion
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Dynamic Spectral Denoising with Global-Context Attention for Multi-Behavior Recommendation
arXiv:2606.02417v1 Announce Type: new Abstract: Multi-behavior recommendation improves target-behavior prediction by exploiting heterogeneous auxiliary feedback (e.g., view, collect, and cart), yet its robustness is undermined by behavior-dependent noise and inconsistency. We argue that the key bottleneck is a representation-level failure caused by two coupled heterogeneities. First, intra-behavior representation entanglement arises when multi-hop propagation blends incidental signals with...