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Dataset Card for UnarXive E5 Index
This repository contains a dense vector index built using the e5-large-v2 model on the abstracts of over 2.3 million arXiv papers in the UnarXive 2024 dataset.
It is designed for neural retrieval, especially in retrieval-augmented generation (RAG) pipelines, scientific QA systems, and dense ranking models.
What's Inside
- Dense embeddings of paper abstracts (
e5-large-v2) - Index format: FAISS (flat or HNSW depending on version)
- Each vector is associated with
paper_id,title, andabstract
Use Cases
- Dense retrieval in scholarly QA or chatbots
- Scientific search engines with semantic understanding
- RAG systems over structured academic corpora
- Paper similarity or clustering
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