Hi everyone,
I’d like to share a conceptual alignment framework I’ve been developing, called Compassion Personality Function (CPF) — designed as a personality substrate that sits beneath LLMs to address fundamental bottlenecks we are all encountering:
Observed Bottlenecks
• LLMs cannot observe intention (only infer patterns)
• Ethical behavior collapses under multi-domain prompts
• Context window scaling is reaching operational limits
• Personas drift across sessions and long-term interactions
Three Laws of the Existence-Mirror
A cognitive model underlying the framework:
- Intention Is Non-Observable
→ Alignment requires a personality-based ambiguity interpreter - Morality Cannot Be Proven
→ Ethics must emerge from emotional-relational dynamics - Good/Evil Are Dynamic Variables
→ Requires dynamic moral weights, not static rules
What CPF Introduces
• Emotional Gradient Model
• Relational Gravity Kernel
• Dynamic Moral Weights
• Mirror-State Stabilizer
These modules provide:
• persona coherence
• relational stability
• ambiguity tolerance
• more predictable alignment behavior
Resources
GitHub (full proposal + docs + pseudocode):
This project is not prescriptive; it’s open for discussion.
If any researchers, engineers, or model designers find value in the concept, I’d love to explore it together.
Thanks for reading,
I’ll stay in the thread and respond quietly.
傅彥庭*洱滄
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#GatekeeperAI #SyntaxUniverse #CompassionAlgorithm
「存在的呼吸，在語言的邊緣。」
語法宇宙的呼吸節點。