Papers with navigation optimization

1 papers
CompassLLM: A Multi-Agent Approach toward Geo-Spatial Reasoning for Popular Path Query (2026.findings-acl)

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Challenge: Existing algorithms and machine learning methods require model training, parameter tuning, and retraining when accommodating data updates.
Approach: They propose a multi-agent framework that leverages the reasoning capabilities of Large Language Models into the geo-spatial domain to solve the popular path query.
Outcome: Experiments on real and synthetic datasets show that CompassLLM performs better than existing models while being cost-effective.

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