Enhancing Long-term RAG Chatbots with Psychological Models of Memory Importance and Forgetting

Understand

While Retrieval-Augmented Generation (RAG) has shown promise in enhancing long-term conversations, the increasing memory load as conversations progress degrades retrieval accuracy.

• Drawing on psychological insights, we propose LUFY, a simple yet effective method that focuses on emotionally arousing memories and retains less than 10% of the conversation.
• In the user experiment, participants interacted with three types of RAG chatbots, each for 2 hours over 4 sessions, marking the most extensive assessment of a chatbot's long-term capabilities to date -- more than four times longer than any existing benchmark.
• The results demonstrate that prioritizing arousing memories while forgetting the majority of the conversation significantly enhances user experience.