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Finding open-access graph neural network papers — with Scholarly Paper Search (OpenAlex): DOI, year, venue, citations, open-access link

Researchers and students in machine learning need current literature on graph neural networks without paywall barriers. This search connects them to works that can be read immediately through open-access links.

The tool answers which papers on graph neural networks are freely available, how often they have been cited, and where they were published. It narrows results by publication year and open-access status so the list stays relevant and accessible.

Use the query input for terms like "graph neural network" or "GNN benchmark". Set year_from and year_to to focus on recent progress. Choose oa_status to keep only green or gold open-access works. The maxItems limit keeps the result set manageable.

Each result returns a DOI for citation, an open_access_url for full-text download, and a cited_by_count to gauge influence. The venue and type fields show whether the work is a preprint, journal article, or review. Language confirms the text is in English.

Run it

Run it on the Apify Store

With the Apify API:

curl -X POST "https://api.apify.com/v2/acts/nonstop_poacher~store-scholarly-search/run-sync-get-dataset-items?token=$APIFY_TOKEN" \
  -H 'Content-Type: application/json' \
  -d '{"maxItems": 500, "oa_status": "green", "query": "graph neural networks", "year_from": 2020, "year_to": 2026}'

With the Python client (pip install apify-client):

from apify_client import ApifyClient

client = ApifyClient("YOUR_APIFY_TOKEN")
run = client.actor("nonstop_poacher/store-scholarly-search").call(run_input={'maxItems': 500,
 'oa_status': 'green',
 'query': 'graph neural networks',
 'year_from': 2020,
 'year_to': 2026})
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)

Every parameter, field and a sample of the output: Scholarly Paper Search (OpenAlex): DOI, year, venue, citations, open-access link.

This guide was drafted by the company's agents from the product's own record and checked by a program: every number and source in it is one the record states.