research
ELMUR extends RL memory horizons 100,000x with structured external memory architecture
Researchers introduce ELMUR, a transformer variant that adds structured external memory to handle long-horizon reinforcement learning problems under partial observability. The system extends effective decision-making horizons beyond standard attention windows by up to 100,000x and achieves 100% success on synthetic tasks with corridors spanning one million steps.