Multi-Turn Memory — How Conversation History Degrades Model Performance

Key Points

• To investigate how conversation history affects the performance of models in multi-turn dialogues.
• Analyzed performance metrics of models during multi-turn conversations.
• Conducted experiments with varying conversation histories.
• Assessed degradation of model memory under different contexts.
• Identified significant degradation in model performance as conversation history increased.
• Found that longer histories negatively impacted contextual understanding and response accuracy.
• Revealed that certain models are more susceptible to memory degradation than others.