WIP
Research
nanoZkinference
Zero-Knowledge Proof system for Transformer model verification with Fisher Information analysis
// DESCRIPTION
Enabling verifiable AI inference through zero-knowledge proofs, ensuring model outputs are trustworthy without revealing model weights.
Problem Statement
How can we prove that a model produced a specific output without revealing the model itself?
Approach
- Circuit Design: zk-SNARK circuits for transformer operations
- Layer-wise Proofs: Generate proofs for each layer independently
- Fisher Analysis: Identify which layers are most important to verify
- Selective Verification: Prove critical layers, trust others
Components
Model → Layer Analysis → Circuit Generation → Proof → Verification
(Fisher Info) (zk-SNARK) (Prover) (Verifier)
Progress
- 8000+ lines of code
- Core infrastructure complete
- Fisher analysis implemented
- Visualization tools ready
// HIGHLIGHTS
- 8000+ LOC research codebase
- Novel selective verification approach
- Extensive documentation (EN/CN)