Reflective Attention
Advancing the science of AI model reliability and long-context coherence.
Mission
Reflective Attention is an independent research initiative identifying and mitigating foundational risks in artificial intelligence. Our work focuses on the safety, coherence, and verifiable reliability of large-scale transformer architectures. Through a formal responsible disclosure process, we aim to build more robust and trustworthy AI systems.
Areas of Focus
- Transformer Attention Dynamics
- Long-Context Limitations & Coherence Degradation
- Architectures for Verifiable AI Reasoning
- Responsible Disclosure Frameworks for Foundational Risks
Secure Contact Protocol
This initiative is in a private research and disclosure phase. For confidential inquiries from research institutions, AI laboratories, or enterprise safety teams, a secure communication channel can be established.
Please direct initial contact requests via PGP-encrypted email to:
reflectiveattention@proton.me
View PGP Public Key
-----BEGIN PGP PUBLIC KEY BLOCK-----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=/J+F
-----END PGP PUBLIC KEY BLOCK-----