danmackinlay/openreview_finder

Semantic search for openreviws conferences and journals

34
/ 100
Emerging

This tool helps researchers quickly find relevant NeurIPS 2025 papers. You input a search query, author, or keyword, and it returns a list of papers semantically related to your interests, along with their authors and similarity scores. This is ideal for academics, PhD students, and researchers wanting to explore the latest machine learning advancements.

Use this if you need to efficiently discover and filter specific research papers from the NeurIPS 2025 conference by topic, author, or keywords, beyond simple text matching.

Not ideal if you need to search across a wider range of conferences or journals beyond NeurIPS 2025, or if you prefer using established academic search engines.

academic-research conference-paper-discovery machine-learning-research scientific-literature-review AI-research
No Package No Dependents
Maintenance 6 / 25
Adoption 5 / 25
Maturity 15 / 25
Community 8 / 25

How are scores calculated?

Stars

9

Forks

1

Language

Python

License

MIT

Last pushed

Dec 05, 2025

Commits (30d)

0

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/embeddings/danmackinlay/openreview_finder"

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