LRE is a CPU-only, language-model-free system that learns which interaction history units are load-bearing. It outperforms baselines in accuracy-cost balance, reducing peak context size by up to 52% and improving task completion by 37% in some cases. LRE achieves superior answer quality with 68% fewer tokens and requires no annotations or neural computation for training.