mshamrai/language-metric-data

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.

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

Code: https://github.com/mshamrai/deep-language-geometry

Gradio Analysis Tool (HF Mirror Space): 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.