Breaking Contextual Inertia: Reinforcement Learning with Single-Turn Anchors for Stable Multi-Turn Interaction

Researchers introduce RLSTA (Reinforcement Learning with Single-Turn Anchors), a new training method that addresses 'contextual inertia' - a problem where AI models fail to integrate new information in multi-turn conversations. The approach uses single-turn reasoning capabilities as anchors to improve multi-turn interaction performance across domains.