SPIN Unprocessed October 27, 2026 ai_technology research
Rethinking Multi-View Fusion for Urban Representation Learning
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arXiv:2610.31850v1 Announce Type: new Abstract: Urban region representation learning encodes heterogeneous urban signals, such as mobility flows, points of interest, and land-use patterns, into unified embeddings for downstream tasks, including check-in prediction, crime forecasting, and service demand estimation. Existing approaches rely on globally shared fusion and joint optimization, implicitly assuming uniform modality importance and naturally balanced multi-objective training. However, urb
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