Location-Aware Language Models via Secondary Embeddings
This work proposes a lightweight, model-agnostic approach for injecting geo-spatial awareness into pretrained embeddings without modifying the tokenizer or requiring costly retraining, and generalizes across multiple model architectures and scales.
G. Srinivasagan, Munir Georges
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