AI RESEARCH
Generative Spatiotemporal Intent Sequence Recommendation via Implicit Reasoning in Amap
arXiv CS.LG
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ArXi:2605.28888v1 Announce Type: cross Real-world user behavior rarely consists of isolated actions; instead, it often forms intent flows governed by spatiotemporal dependencies. To provide integrated service recommendations, we focus on the task of Generative Spatiotemporal Intent Sequence Recommendation (GSISR), which aims to generate intent sequences that are logically coherent and physically executable within complex spatiotemporal contexts.