metaphacts/linkedpaperswithcode

Code for generating Linked Papers with Code a high-quality RDF knowledge graph with metadata about the machine learning landscape.

40
/ 100
Emerging

This project helps machine learning researchers, data scientists, and academics explore the vast landscape of ML research. It takes raw data from Papers With Code, processes it into a structured knowledge graph, and outputs comprehensive information about ML publications, including tasks, datasets, methods, and evaluation results. You would use this if you need a structured, queryable view of ML research to find relevant papers, understand method effectiveness, or analyze research trends.

Use this if you need a structured, interconnected dataset of machine learning research to query and analyze trends, rather than just browsing individual papers.

Not ideal if you're only looking for a simple keyword search across paper titles or abstracts, as the full power of the knowledge graph would be underutilized.

machine-learning-research academic-research literature-review research-trends data-science
No Package No Dependents
Maintenance 6 / 25
Adoption 4 / 25
Maturity 16 / 25
Community 14 / 25

How are scores calculated?

Stars

8

Forks

3

Language

HTML

License

MIT

Last pushed

Oct 22, 2025

Commits (30d)

0

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/metaphacts/linkedpaperswithcode"

Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.