StillMe: A Practical Framework for Building Transparent, Validated Retrieval-Augmented Generation Systems

StillMe is a transparency-first framework designed to transform commercial LLMs into fully auditable systems without any model training or labeled datasets.
   
   This paper introduces:
   - A multi-layer Validation Chain to reduce hallucination
   - A continuous learning pipeline updating every 4 hours (RSS, arXiv, CrossRef, Wikipedia)
   
   Evaluation Results (Updated):
   - Accuracy: 35% (20-question subset), 13.5% (full 790-question evaluation)
   - Citation Rate: 91.1% (full evaluation)
   - Transparency Score: 85.8% (full evaluation)
   - Validation Pass Rate: 93.9% (full evaluation)