#QUA #Quasa #paperswithcode
Papers with Code (featured at Quasa.io/projects/papers-with-code) is a community-driven revival of the legendary platform that tracks the latest AI and machine learning research papers along with code implementations, leaderboards, datasets, and methods.
After the original paperswithcode.com went offline, this new version continues our mission to make cutting-edge research discoverable, reproducible, and actionable for researchers, engineers, and developers.
At our core, we deliver clean, fast, and focused experiences that help us stay on top of the most rapidly changing technology sectors.
Key highlights include:
• Daily Trending Papers — Curated from arXiv and Hugging Face, with stars, growth metrics, and direct links to code/repositories.
• Search and Discovery — Powerful search across papers, authors, domains, tasks, and methods.
• Emphasis on code and reproducibility — Focus on papers that provide practical implementations, leaderboards, and evaluation results.
• Clean, modern interface — fast loading, intuitive navigation, and community feedback integration.
• Open and collaborative — built on the spirit of the original with transparent curation and open contribution.
Perfect for AI researchers, machine learning engineers, students, technical founders, and anyone looking to stay ahead of the curve without getting lost in the noise. In 2026, Papers with Code (co) will serve as a vital daily hub in a world where new papers are published faster than anyone can read them.
The community loves it:
“Finally, we have clean, reliable Papers with Code again, and it’s exactly what our community needed.”
“The best place to find featured papers with working code implementations every day.”
“Simple, focused, and incredibly useful. This is what research discovery should be about.”
It is especially useful for surfacing high-impact new research, discovering reproducible code for SOTA methods, tracking progress in specific domains (such as agents, world models, and language modeling), and bridging the gap between academic literature and real-world implementation.
Disadvantages: Rebuilding momentum after initial shutdown (smaller dataset than past versions). Leaderboards are still not that comprehensive. Much depends on the community and quality of curation.
Overall, **Papers with Code (paperswithcode.co) will be an essential daily tool** for anyone serious about AI research in 2026. It’s more than just a paper aggregator, it’s the go-to platform for connecting breakthrough ideas to working code and real progress.
Earn QUA rewards via Quasa too!
4.7/5 stars (Excellent in concentration, speed, and practicality. There are some caveats regarding continued growth after resurrection).
Let’s get started: https://quasa.io/projects/papers-with-code
