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      "statement": "# MultiBiSage: bipartite-view fusion for heterogeneous recommendation graphs\n\nDecomposed heterogeneous entity interactions into bipartite views, aggregated each view's sampled visual/textual neighborhood with a Transformer and fused the resulting view embeddings through another attention layer.\n\n## Scientific scope\n\nA distinct heterogeneous-view fusion extension, not another count for PinSage deployment or its original sampler. Reuses Pixie and distributed data workflows. View decomposition, stored neighborhoods and selected losses constrain expressiveness and cost; v1's template DOI/venue placeholders are not exported as valid publication facts.\n\n## Reading status\n\nThis is a source-linked WRS catalogue note. A full explanatory guide and independent scientific reconstruction have not been completed for this entry. Read the identified original work for its complete narrative and arguments.\n\n## People and systems\n\nSaket Gurukar; Nikil Pancha; Andrew Zhai; Eric Kim; Samson Hu; Srinivasan Parthasarathy; Charles Rosenberg; Jure Leskovec\n\nSource-listed authors or explicitly credited technical contributors for the cited versions. Family entries retain source-specific attribution; a combined list is not one original-paper byline or equal individual work. Names alone do not establish resolved identities.\n\n\n\n## Original sources\n\n- [MultiBiSage: A Web-Scale Recommendation System Using Multiple Bipartite Graphs at Pinterest](https://arxiv.org/abs/2205.10666v1)\n",
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