| | --- |
| | license: mit |
| | task_categories: |
| | - feature-extraction |
| | tags: |
| | - multilingual |
| | - llm |
| | - linguistics |
| | - embeddings |
| | --- |
| | |
| | This dataset contains the computed language latent vectors (binary vectors, Euclidean vectors, and distances) as presented in the paper [Deep Language Geometry: Constructing a Metric Space from LLM Weights](https://huggingface.co/papers/2508.11676). |
| |
|
| | The paper introduces a novel framework that utilizes the internal weight activations of Large Language Models (LLMs) to construct a metric space of languages. This dataset makes the automatically derived high-dimensional vector representations for 106 languages publicly available, capturing intrinsic language characteristics that reflect linguistic phenomena. |
| |
|
| | **Paper:** [Deep Language Geometry: Constructing a Metric Space from LLM Weights](https://huggingface.co/papers/2508.11676) |
| |
|
| | **Code:** [https://github.com/mshamrai/deep-language-geometry](https://github.com/mshamrai/deep-language-geometry) |
| |
|
| | **Gradio Analysis Tool (Hugging Face Space):** [https://huggingface.co/spaces/mshamrai/language-metric-analysis](https://huggingface.co/spaces/mshamrai/language-metric-analysis) |
| |
|
| | ### Dataset Contents |
| |
|
| | The dataset includes: |
| | - Calculated binary vectors |
| | - Euclidean vectors |
| | - Distances between languages |
| |
|
| | These components can be used to analyze and visualize inter-language connections and linguistic families. |
