Geographical Location Representation

Geographical location representation focuses on effectively encoding and utilizing geographic information within computational models, aiming to improve the accuracy and efficiency of various location-based applications. Current research emphasizes leveraging large language models and transformer architectures to generate robust geolocation representations from textual and visual data, while also addressing biases inherent in training datasets and improving generalization across diverse conditions. This work is crucial for advancing applications in geospatial analysis, improving the performance of spatio-temporal forecasting models, and mitigating biases in AI systems that generate geographic content.