❝ In the era of global AI governance, reproducibility, transparency, and ethical openness are no longer suggestions—they are obligations. ❞

Publishing on Ready Tensor isn’t just about uploading your model or dataset. It’s about advancing the frontier of open, ethical, and high-impact artificial intelligence. Your publication becomes part of a collective scientific archive used by global researchers, policy institutions, industry developers, and innovators.

Whether you're contributing a novel transformer architecture, an automation pipeline, or a large-scale multilingual dataset, this article gives you a clear, AI-native, globally aware checklist to follow—rooted in the principles of scientific reproducibility, EU AI policy frameworks, and open-source collaboration.

Why Ready Tensor Is More Than a Platform.

Ready Tensor is not just a repository. It’s an infrastructure node in the global AI knowledge commons. Your work here:

• Contributes to global AI safety standards
• Interfaces with policy frameworks like the EU AI Act and UNESCO AI Ethics
• Builds trust through reproducibility, licensing clarity, and open collaboration
• Enables industrial, academic, and regulatory uptake

This article is your definitive checklist + strategic guide to publishing AI models, datasets, or systems on Ready Tensor with international credibility, technical integrity, and social responsibility.

The 9-Point Protocol for Publishing on Ready Tensor

"Each point below is both a best practice and a signal to the world: your work is built for public value and rigorous accountability."

🧠 Title = Your Intellectual & Policy Signal.

Your title is metadata. It will be indexed by:

• Google Scholar & ArXiv
• AI policy trackers (e.g., OECD.AI)
• GitHub repositories & grant databases

A good title is:

• Technically precise (e.g., model type, domain)
• Societally situated (e.g., “AI for Disaster Risk Reduction”)
• Policy-aligned (e.g., references to GDPR, AI Act)

💡 Examples:

“Federated Vision Transformers for GDPR-Compliant Traffic Surveillance in the EU”
“Multilingual LLM Alignment with EU-AI Risk Tiers: A Conformity-Aware Benchmark”