EviSnap creates cross-domain recommendations whose scores decompose exactly into evidence-cited concept contributions via offline LLM facet extraction, clustering, and linear transfer.
InProceedings of the 2016 Conference on Empirical Methods in Natu- ral Language Processing, pages 107–117
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EviSnap: Faithful Evidence-Cited Explanations for Cold-Start Cross-Domain Recommendation
EviSnap creates cross-domain recommendations whose scores decompose exactly into evidence-cited concept contributions via offline LLM facet extraction, clustering, and linear transfer.