3 papers
cs.LG2026
Towards Efficient and Evidence-grounded Mobility Prediction with LLM-Driven Agent
Linyao Chen, Qinlao Zhao, Zechen Li +7
Individual-level mobility prediction is central to urban simulation, transportation planning, and policy analysis. Supervised sequence models achieve strong accuracy but require ta…
cs.IR2026
Next Point-of-interest (POI) Recommendation Model Based on Multi-modal Spatio-temporal Context Feature Embedding
Lingyu Zhang, Pengfei Xu, Rui Ban +4
Predicting the next pickup location of individual users is a fundamental problem in intelligent mobility systems, which requires modeling personalized travel behaviors under comple…
cs.LG2025
A Knowledge-Guided Cross-Modal Feature Fusion Model for Local Traffic Demand Prediction
Lingyu Zhang, Pengfei Xu, Guobin Wu +4
Traffic demand prediction plays a critical role in intelligent transportation systems. Existing traffic prediction models primarily rely on temporal traffic data, with limited effo…