  Understanding the representations of different languages in multilingual
language models is essential for comprehending their cross-lingual properties,
predicting their performance on downstream tasks, and identifying any biases
across languages. In our study, we analyze the geometry of three multilingual
language models in Euclidean space and find that all languages are represented
by unique geometries. Using a geometric separability index we find that
although languages tend to be closer according to their linguistic family, they
are almost separable with languages from other families. We also introduce a
Cross-Lingual Similarity Index to measure the distance of languages with each
other in the semantic space. Our findings indicate that the low-resource
languages are not represented as good as high resource languages in any of the
models
