Learning to Forget: Sleep-Inspired Memory Consolidation for Resolving Proactive Interference in Large Language Models

Researchers developed SleepGate, a biologically-inspired framework that significantly improves large language model memory by mimicking sleep-based consolidation to resolve proactive interference. The system achieved 99.5% retrieval accuracy compared to less than 18% for existing methods in experimental testing.