GaGA is an MLLM-based interactive geolocation system that improves country-level accuracy by 4.57% and city-level accuracy by 2.92% over OSV-5M-Baseline on a reproduced GWS15k benchmark.
Twitter User Geolocation Using a Unified Text and Network Prediction Model
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abstract
We propose a label propagation approach to geolocation prediction based on Modified Adsorption, with two enhancements:(1) the removal of "celebrity" nodes to increase location homophily and boost tractability, and (2) he incorporation of text-based geolocation priors for test users. Experiments over three Twitter benchmark datasets achieve state-of-the-art results, and demonstrate the effectiveness of the enhancements.
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Towards Interactive Global Geolocation Assistant
GaGA is an MLLM-based interactive geolocation system that improves country-level accuracy by 4.57% and city-level accuracy by 2.92% over OSV-5M-Baseline on a reproduced GWS15k benchmark.