DeRes decouples residual stability and adaptivity via identity and block-attention paths with SiLU pointwise attention, delivering up to 0.32% AUC gains and steeper scaling laws on industrial and public CTR datasets.
Unimixer: A unified architecture for scaling laws in recommendation systems.arXiv preprint arXiv:2604.00590, 2026
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RankUp raises effective rank of representations in deep MetaFormer recommenders via randomized splitting and multi-embeddings, delivering 2-5% GMV gains in production deployments at Weixin.
SinkRec proposes a memory-conditioned architecture with TDGD to mitigate semantic state sink in linear attention for long-sequence recommendation.
citing papers explorer
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DeRes: Decoupling Residual Stability and Adaptivity for Scalable CTR Prediction
DeRes decouples residual stability and adaptivity via identity and block-attention paths with SiLU pointwise attention, delivering up to 0.32% AUC gains and steeper scaling laws on industrial and public CTR datasets.
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RankUp: Towards High-rank Representations for Large Scale Advertising Recommender Systems
RankUp raises effective rank of representations in deep MetaFormer recommenders via randomized splitting and multi-embeddings, delivering 2-5% GMV gains in production deployments at Weixin.
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SinkRec: Mitigating Semantic State Sink in Long Sequence Recommendation with Memory-Conditioned Gated Delta Networks
SinkRec proposes a memory-conditioned architecture with TDGD to mitigate semantic state sink in linear attention for long-sequence recommendation.