Improve dataset card: Add paper, code, Gradio space links, and update metadata

README.md

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-license: apache-2.0
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+---
+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.