MeMo Boosts LLM Performance 26% Without Retraining

MeMo is a new framework that lets teams update large language models with fresh knowledge without costly retraining or complex retrieval pipelines. It works by encoding new information into a separate, smaller memory model that runs alongside the main LLM, supporting both open- and closed-source systems. The modular approach avoids catastrophic forgetting linked to direct fine-tuning and handles noisy retrieval conditions reliably. Experiments show a 26% performance improvement, offering enterprises a practical and cost-effective path to continuous knowledge updates.