ReMe: Scaffolding Personalized Cognitive Training via Controllable LLM-Mediated Conversations

1. 1Utilize large language models (LLMs) to generate interactive conversations for cognitive training
2. 2Implement controllable mechanisms to ensure task structure and personalization
3. 3Design personalized cognitive training programs using LLM-mediated conversations
4. 4Evaluate the effectiveness of ReMe in improving cognitive abilities and user engagement

AI engineers and cognitive training specialists can benefit from this approach to create more engaging and personalized training programs, improving user adherence and outcomes

💡 Controllable LLM-mediated conversations can enhance personalized cognitive training

🤖 ReMe: personalized cognitive training via controllable LLM conversations