arxiv

arXiv Research

Search and retrieve academic papers from arXiv via their free REST API. No API key, no dependencies — just curl.

Quick Reference

Action	Command
Search papers	curl "https://export.arxiv.org/api/query?search_query=all:QUERY&max_results=5"
Get specific paper	curl "https://export.arxiv.org/api/query?id_list=2402.03300"
Read abstract (web)	web_extract(urls=["https://arxiv.org/abs/2402.03300"])
Read full paper (PDF)	web_extract(urls=["https://arxiv.org/pdf/2402.03300"])

Searching Papers

The API returns Atom XML. Parse with grep/sed or pipe through python3 for clean output.

Basic search

curl -s "https://export.arxiv.org/api/query?search_query=all:GRPO+reinforcement+learning&max_results=5"

Clean output (parse XML to readable format)

curl -s "https://export.arxiv.org/api/query?search_query=all:GRPO+reinforcement+learning&max_results=5&sortBy=submittedDate&sortOrder=descending" | python3 -c "
import sys, xml.etree.ElementTree as ET
ns = {'a': 'http://www.w3.org/2005/Atom'}
root = ET.parse(sys.stdin).getroot()
for i, entry in enumerate(root.findall('a:entry', ns)):
    title = entry.find('a:title', ns).text.strip().replace('\n', ' ')
    arxiv_id = entry.find('a:id', ns).text.strip().split('/abs/')[-1]
    published = entry.find('a:published', ns).text[:10]
    authors = ', '.join(a.find('a:name', ns).text for a in entry.findall('a:author', ns))
    summary = entry.find('a:summary', ns).text.strip()[:200]
    cats = ', '.join(c.get('term') for c in entry.findall('a:category', ns))
    print(f'{i+1}. [{arxiv_id}] {title}')
    print(f'   Authors: {authors}')
    print(f'   Published: {published} | Categories: {cats}')
    print(f'   Abstract: {summary}...')
    print(f'   PDF: https://arxiv.org/pdf/{arxiv_id}')
    print()
"

Search Query Syntax

Prefix	Searches	Example
all:	All fields	all:transformer+attention
ti:	Title	ti:large+language+models
au:	Author	au:vaswani
abs:	Abstract	abs:reinforcement+learning
cat:	Category	cat:cs.AI
co:	Comment	co:accepted+NeurIPS

Boolean operators

# AND (default when using +)
search_query=all:transformer+attention

# OR
search_query=all:GPT+OR+all:BERT

# AND NOT
search_query=all:language+model+ANDNOT+all:vision

# Exact phrase
search_query=ti:"chain+of+thought"

# Combined
search_query=au:hinton+AND+cat:cs.LG

Sort and Pagination

Parameter	Options
sortBy	relevance, lastUpdatedDate, submittedDate
sortOrder	ascending, descending
start	Result offset (0-based)
max_results	Number of results (default 10, max 30000)

# Latest 10 papers in cs.AI
curl -s "https://export.arxiv.org/api/query?search_query=cat:cs.AI&sortBy=submittedDate&sortOrder=descending&max_results=10"

Fetching Specific Papers

# By arXiv ID
curl -s "https://export.arxiv.org/api/query?id_list=2402.03300"

# Multiple papers
curl -s "https://export.arxiv.org/api/query?id_list=2402.03300,2401.12345,2403.00001"

BibTeX Generation

After fetching metadata for a paper, generate a BibTeX entry:

{% raw %}

curl -s "https://export.arxiv.org/api/query?id_list=1706.03762" | python3 -c "
import sys, xml.etree.ElementTree as ET
ns = {'a': 'http://www.w3.org/2005/Atom', 'arxiv': 'http://arxiv.org/schemas/atom'}
root = ET.parse(sys.stdin).getroot()
entry = root.find('a:entry', ns)
if entry is None: sys.exit('Paper not found')
title = entry.find('a:title', ns).text.strip().replace('\n', ' ')
authors = ' and '.join(a.find('a:name', ns).text for a in entry.findall('a:author', ns))
year = entry.find('a:published', ns).text[:4]
raw_id = entry.find('a:id', ns).text.strip().split('/abs/')[-1]
cat = entry.find('arxiv:primary_category', ns)
primary = cat.get('term') if cat is not None else 'cs.LG'
last_name = entry.find('a:author', ns).find('a:name', ns).text.split()[-1]
print(f'@article{{{last_name}{year}_{raw_id.replace(\".\", \"\")},')
print(f'  title     = {{{title}}},')
print(f'  author    = {{{authors}}},')
print(f'  year      = {{{year}}},')
print(f'  eprint    = {{{raw_id}}},')
print(f'  archivePrefix = {{arXiv}},')
print(f'  primaryClass  = {{{primary}}},')
print(f'  url       = {{https://arxiv.org/abs/{raw_id}}}')
print('}')
"

{% endraw %}

Reading Paper Content

After finding a paper, read it:

# Abstract page (fast, metadata + abstract)
web_extract(urls=["https://arxiv.org/abs/2402.03300"])

# Full paper (PDF → markdown via Firecrawl)
web_extract(urls=["https://arxiv.org/pdf/2402.03300"])

For local PDF processing, see the ocr-and-documents skill.

Common Categories

Category	Field
cs.AI	Artificial Intelligence
cs.CL	Computation and Language (NLP)
cs.CV	Computer Vision
cs.LG	Machine Learning
cs.CR	Cryptography and Security
stat.ML	Machine Learning (Statistics)
math.OC	Optimization and Control
physics.comp-ph	Computational Physics

Full list: https://arxiv.org/category_taxonomy

Helper Script

The scripts/search_arxiv.py script handles XML parsing and provides clean output:

python scripts/search_arxiv.py "GRPO reinforcement learning"
python scripts/search_arxiv.py "transformer attention" --max 10 --sort date
python scripts/search_arxiv.py --author "Yann LeCun" --max 5
python scripts/search_arxiv.py --category cs.AI --sort date
python scripts/search_arxiv.py --id 2402.03300
python scripts/search_arxiv.py --id 2402.03300,2401.12345

No dependencies — uses only Python stdlib.

---

Semantic Scholar (Citations, Related Papers, Author Profiles)

arXiv doesn't provide citation data or recommendations. Use the Semantic Scholar API for that — free, no key needed for basic use (1 req/sec), returns JSON.

Get paper details + citations

# By arXiv ID
curl -s "https://api.semanticscholar.org/graph/v1/paper/arXiv:2402.03300?fields=title,authors,citationCount,referenceCount,influentialCitationCount,year,abstract" | python3 -m json.tool

# By Semantic Scholar paper ID or DOI
curl -s "https://api.semanticscholar.org/graph/v1/paper/DOI:10.1234/example?fields=title,citationCount"

Get citations OF a paper (who cited it)

curl -s "https://api.semanticscholar.org/graph/v1/paper/arXiv:2402.03300/citations?fields=title,authors,year,citationCount&limit=10" | python3 -m json.tool

Get references FROM a paper (what it cites)

curl -s "https://api.semanticscholar.org/graph/v1/paper/arXiv:2402.03300/references?fields=title,authors,year,citationCount&limit=10" | python3 -m json.tool

Search papers (alternative to arXiv search, returns JSON)

curl -s "https://api.semanticscholar.org/graph/v1/paper/search?query=GRPO+reinforcement+learning&limit=5&fields=title,authors,year,citationCount,externalIds" | python3 -m json.tool

Get paper recommendations

curl -s -X POST "https://api.semanticscholar.org/recommendations/v1/papers/" \
  -H "Content-Type: application/json" \
  -d '{"positivePaperIds": ["arXiv:2402.03300"], "negativePaperIds": []}' | python3 -m json.tool

Author profile

curl -s "https://api.semanticscholar.org/graph/v1/author/search?query=Yann+LeCun&fields=name,hIndex,citationCount,paperCount" | python3 -m json.tool

Useful Semantic Scholar fields

title, authors, year, abstract, citationCount, referenceCount, influentialCitationCount, isOpenAccess, openAccessPdf, fieldsOfStudy, publicationVenue, externalIds (contains arXiv ID, DOI, etc.)

---

Complete Research Workflow

1. Discover: python scripts/search_arxiv.py "your topic" --sort date --max 10
2. Assess impact: curl -s "https://api.semanticscholar.org/graph/v1/paper/arXiv:ID?fields=citationCount,influentialCitationCount"
3. Read abstract: web_extract(urls=["https://arxiv.org/abs/ID"])
4. Read full paper: web_extract(urls=["https://arxiv.org/pdf/ID"])
5. Find related work: curl -s "https://api.semanticscholar.org/graph/v1/paper/arXiv:ID/references?fields=title,citationCount&limit=20"
6. Get recommendations: POST to Semantic Scholar recommendations endpoint
7. Track authors: curl -s "https://api.semanticscholar.org/graph/v1/author/search?query=NAME"

Rate Limits

API	Rate	Auth
arXiv	~1 req / 3 seconds	None needed
Semantic Scholar	1 req / second	None (100/sec with API key)

Notes

• arXiv returns Atom XML — use the helper script or parsing snippet for clean output
• Semantic Scholar returns JSON — pipe through python3 -m json.tool for readability
• arXiv IDs: old format (hep-th/0601001) vs new (2402.03300)
• PDF: https://arxiv.org/pdf/{id} — Abstract: https://arxiv.org/abs/{id}
• HTML (when available): https://arxiv.org/html/{id}
• For local PDF processing, see the ocr-and-documents skill

ID Versioning

• arxiv.org/abs/1706.03762 always resolves to the latest version
• arxiv.org/abs/1706.03762v1 points to a specific immutable version
• When generating citations, preserve the version suffix you actually read to prevent citation drift (a later version may substantially change content)
• The API <id> field returns the versioned URL (e.g., http://arxiv.org/abs/1706.03762v7)

Withdrawn Papers

Papers can be withdrawn after submission. When this happens:

• The <summary> field contains a withdrawal notice (look for "withdrawn" or "retracted")
• Metadata fields may be incomplete
• Always check the summary before treating a result as a valid paper