Multi-Turn Conversation
An extended dialogue between a user and AI spanning multiple exchanges, requiring context tracking across turns.
Overview
Multi-turn conversation refers to an ongoing dialogue where the AI maintains context across multiple user-assistant exchanges. Each new message must be understood in the context of the full conversation history, including references, topic shifts, and evolving requirements.
Technical Challenges
Key challenges include managing growing context length (conversation history consuming the context window), coreference resolution (understanding 'it', 'that'), maintaining consistency across turns, handling topic switches, and memory management for very long conversations. Techniques include conversation summarization, sliding window approaches, and explicit memory systems.