Local AI Recursive Feedback Loop & Semantic Embedding Audit Tool

Cycle Configuration GEN-0 TO GEN-5

Benchmark Dataset Preset

Recursive Generation Cycles 5 Cycles

Filtering Cosine Similarity Threshold 0.85

Synthetic Mutation Rate (Noise) 0.15

Active Seed Documents (4)

Semantic Embedding Drift

0.182

Distance from Gen-0 Baseline

Contamination Rate

24.5%

Synthetic Data Saturation

Loop State

STABLE

Mode Collapse Avoided

2D EMBEDDING VECTOR SPACE (PCA REDUCTION) D3 ENGINE

PAIR-WISE COSINE SIMILARITY MATRIX GEN-0 vs GEN-5

AUDIT VERDICT: SEMANTIC DRIFT BOUNDS MET

Recursive execution across 5 generations demonstrated a total semantic embedding drift of 0.182. Model self-distillation filter maintained variance above the 0.85 cosine similarity floor, preserving key alignment vectors.

PROVED: RECURSIVE DECAY QUANTIFIED