AINeutralarXiv – CS AI · Mar 34/103
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Adaptive Location Hierarchy Learning for Long-Tailed Mobility Prediction
Researchers propose ALOHA, an architecture-agnostic plugin that improves human mobility prediction models by addressing long-tailed distribution bias in location visits. The system uses Large Language Models and Chain-of-Thought prompts to construct location hierarchies and demonstrates up to 16.59% performance improvements across multiple state-of-the-art models.