CaST-POI: Candidate-Conditioned Spatiotemporal Modeling for Next POI Recommendation

arXiv:2604.20845 · cs.IR, cs.AI · Submitted 2026-02-10 · Read on arXiv

cs.IR, cs.AI

Submitted: 2026-02-10

Updated: 2026-09-01

Code: https://github.com/YuZhenyuLindy/CaST-POI

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Embeddings — 8× in this paper · explained in 2 episodes
• Next Point-of-Interest — 6× in this paper
• Ablation — 5× in this paper · explained in 1 episode
• Transformer — 5× in this paper · explained in 2 episodes
• Benchmark — 4× in this paper · explained in 2 episodes
• Robustness — 4× in this paper · explained in 5 episodes
• Sparsity — 4× in this paper · explained in 4 episodes
• Ablation study — 3× in this paper · explained in 1 episode
• Accuracy — 3× in this paper · explained in 1 episode
• Representation Learning — 3× in this paper · explained in 2 episodes
• Contrastive Learning — 2× in this paper · explained in 5 episodes
• Generalization — 2× in this paper · explained in 13 episodes
• Ablation Studies — 1× in this paper · explained in 1 episode
• Adam — 1× in this paper · explained in 2 episodes
• AdamW Optimizer — 1× in this paper · explained in 1 episode
• Attention Mechanism — 1× in this paper · explained in 2 episodes
• Core — 1× in this paper · explained in 2 episodes
• Data Augmentation — 1× in this paper · explained in 7 episodes
• Diffusion Model — 1× in this paper · explained in 8 episodes
• Distribution Shift — 1× in this paper · explained in 5 episodes
• Large Language Models (LLMs) — 1× in this paper · explained in 6 episodes
• Mean Reciprocal Rank — 1× in this paper
• Multi-Agent Framework — 1× in this paper · explained in 3 episodes
• Nadia — 1× in this paper · explained in 2 episodes

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