AI RESEARCH
MT-OSC: Path for LLMs that Get Lost in Multi-Turn Conversation
arXiv CS.CL
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ArXi:2604.08782v1 Announce Type: new Large language models (LLMs) suffer significant performance degradation when user instructions and context are distributed over multiple conversational turns, yet multi-turn (MT) interactions dominate chat interfaces. The routine approach of appending full chat history to prompts rapidly exhausts context windows, leading to increased latency, higher computational costs, and diminishing returns as conversations extend. We