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Researchers Identify 'Contextual Inertia' Bug in LLMs During Multi-Turn Conversations
Researchers have identified a critical failure mode in large language models called 'contextual inertia'—where models ignore new information in multi-turn conversations and rigidly stick to previous reasoning. A new training method called RLSTA uses single-turn performance as an anchor to stabilize multi-turn reasoning and recover performance lost to this phenomenon.