OnePred: Next-Query Prediction via Recursive Intent Memory in Multi-Turn Conversations

📰 ArXiv cs.AI

Learn to predict next queries in multi-turn conversations using OnePred, enhancing proactive interaction in LLM conversational systems

advanced Published 25 May 2026
Action Steps
  1. Implement OnePred using recursive intent memory to predict next queries
  2. Train the model on multi-turn dialogue datasets
  3. Evaluate the model's performance using dedicated benchmarks
  4. Fine-tune the model for improved efficiency and quality
  5. Integrate the model into LLM conversational systems
Who Needs to Know This

NLP engineers and researchers on a team benefit from this knowledge to improve conversational AI systems, while product managers can leverage it to enhance user experience

Key Insight

💡 Recursive intent memory is key to predicting next queries in multi-turn conversations

Share This
🤖 OnePred predicts next queries in conversations! #LLM #ConversationalAI

Key Takeaways

Learn to predict next queries in multi-turn conversations using OnePred, enhancing proactive interaction in LLM conversational systems

Read full paper → ← Back to Reads

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