3 papers
cs.IR2026
SPAR: Enhancing Industrial-Scale Generative POI Recommendation via Real-World Spatial Perception
Fangye Wang, Yunjin Gu, Haowen Lin +4
Generative Point-of-Interest (POI) recommendation, autoregressively generating a target POI's semantic ID (SID), holds great promise for Location-Based Services, where a recommenda…
cs.IR2026
HF-SID: High-Fidelity Semantic IDs for Generative Retrieval in Location-Based Services
Haowen Lin, Jing Li, Zhibin Hao +5
Generative retrieval has attracted increasing attention in Location-Based Services (LBS), where each Point-of-Interest (POI) is represented as a Semantic ID (SID). As the SID is th…
cs.IR2026
GeoGR: Enabling Spatio-Temporal Aware Industrial-scale Generative POI Recommendations
Fangye Wang, Haowen Lin, Yifang Yuan +4
Next Point-of-Interest (POI) prediction is a fundamental task in location-based services (LBS), especially critical for large-scale navigation platforms such as AMAP that serve bil…