#multi-turn-interaction2 articles

2 articles

AIBullisharXiv – CS AI · 4h ago2

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InfoPO: Information-Driven Policy Optimization for User-Centric Agents

Researchers introduce InfoPO (Information-Driven Policy Optimization), a new method that improves AI agent interactions by using information-gain rewards to identify valuable conversation turns. The approach addresses credit assignment problems in multi-turn interactions and outperforms existing baselines across diverse tasks including intent clarification and collaborative coding.

AIBullisharXiv – CS AI · 4h ago1

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Words & Weights: Streamlining Multi-Turn Interactions via Co-Adaptation

Researchers introduce ROSA2, a framework that improves Large Language Model interactions by simultaneously optimizing both prompts and model parameters during test-time adaptation. The approach outperformed baselines by 30% on mathematical tasks while reducing interaction turns by 40%.