Co-LMLM: Continuous-Query Limited Memory Language Models
CO-LMLM introduces a Limited Memory Language Model that externalizes knowledge into a searchable database instead of memorizing it. It uses continuous keys and textual knowledge values to allow flexible, low-cost vector queries during generation. This enables human-readable, attributable knowledge retrieval while maintaining the controllability and editability benefits of LMLMs.