Arxiv paper lookup

Arxiv Paper Lookup Skill

Overview

When files are named with arxiv IDs (e.g., 2305.12773v1.pdf), you can extract metadata via the arxiv API to classify papers by subject without downloading/reading the full PDF.

Extracting Arxiv ID from Filename

import re

def extract_arxiv_id(filename):
    # Strip path and extension
    base = os.path.basename(filename).replace('.pdf', '')
    # Remove version suffix like v1, v2, v3
    arxiv_id = re.sub(r'v\d+$', '', base)
    return arxiv_id  # e.g., "2305.12773"

Fetching Metadata via Arxiv API

import urllib.request
import xml.etree.ElementTree as ET

def fetch_arxiv_metadata(arxiv_id):
    url = f"http://export.arxiv.org/api/query?id_list={arxiv_id}"
    with urllib.request.urlopen(url) as response:
        data = response.read().decode('utf-8')

    root = ET.fromstring(data)
    ns = {'atom': 'http://www.w3.org/2005/Atom'}
    entry = root.find('atom:entry', ns)
    if entry is None:
        return None

    title = entry.find('atom:title', ns).text.strip()
    summary = entry.find('atom:summary', ns).text.strip()
    categories = [c.get('term') for c in entry.findall('{http://arxiv.org/schemas/atom}primary_category', ns)]

    return {'title': title, 'summary': summary, 'categories': categories}

Batch Fetching (up to 100 IDs at once)

def fetch_batch(arxiv_ids):
    id_list = ','.join(arxiv_ids)
    url = f"http://export.arxiv.org/api/query?id_list={id_list}&max_results={len(arxiv_ids)}"
    # ... parse response

Classification Strategy

• Use title + abstract keywords to classify
• Common arxiv categories: cs.CL, cs.AI (LLM), quant-ph (quantum), gr-qc (black hole), q-bio (DNA/biology)
• Titles are usually sufficient for classification

Rate Limiting

• Arxiv API allows ~3 requests/second
• Add time.sleep(0.5) between batch requests
• Batch up to 100 IDs per request