[R] Larimar: Large Language Models with Episodic Memory Control

**Paper**: [https://arxiv.org/abs/2403.11901](https://arxiv.org/abs/2403.11901)

**Abstract**:

>Efficient and accurate updating of knowledge stored in Large Language Models (LLMs) is one of the most pressing research challenges today. This paper presents **Larimar** \- a novel, brain-inspired architecture for enhancing LLMs with a distributed episodic memory. Larimar's memory allows for dynamic, one-shot updates of knowledge without the need for computationally expensive re-training or fine-tuning. Experimental results on multiple fact editing benchmarks demonstrate that Larimar attains accuracy comparable to most competitive baselines, even in the challenging …

abstract architecture brain brain-inspired challenges distributed dynamic experimental fine-tuning knowledge language language models large language large language models llms machinelearning memory novel paper research results training updates