Structured Memory Mechanisms for Stable Context Representation in Large Language Models

Understand

This paper addresses the limitations of large language models in understanding long-term context.

• It proposes a model architecture equipped with a long-term memory mechanism to improve the retention and retrieval of semantic information across paragraphs and dialogue turns.
• The model integrates explicit memory units, gated writing mechanisms, and attention-based reading modules.
• A forgetting function is introduced to enable dynamic updates of memory content, enhancing the model's ability to manage historical information.