arXiv Machine Learning August 18, 2026 By Burak Tamer, Wolfram H\"opken, Zehui Wang

POI Recommendation with LLM-Augmented Multi-Graph Learning and Contrastive Alignment

Read the original on arXiv Machine Learning →

arXiv:2608. 16407v1 Announce Type: cross Abstract: Point-of-interest (POI) recommendation models based on graph neural networks achieve strong performance by propagating collaborative signals over user-item interactions, yet they struggle with the cold-start problem, where items with few or no interactions are not represented.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

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