June 7, 2024, 4:44 a.m. | Alameen Najjar

cs.LG updates on arXiv.org arxiv.org

arXiv:2406.04029v1 Announce Type: cross
Abstract: We empirically demonstrate that a transformer pre-trained on country-scale unlabeled human mobility data learns embeddings capable, through fine-tuning, of developing a deep understanding of the target geography and its corresponding mobility patterns. Utilizing an adaptation framework, we evaluate the performance of our pre-trained embeddings in encapsulating a broad spectrum of concepts directly and indirectly related to human mobility. This includes basic notions, such as geographic location and distance, and extends to more complex constructs, such …

abstract arxiv country cs.ai cs.cy cs.lg data embeddings fine-tuning framework geography human mobility patterns performance scale through transformer type understanding

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