LLM Parkinsonism: executive-control failure, token-inefficient persistence, and an uncertainty-aware global executive control architecture for autonomous language-model agents
Read the original at arxiv.org→arXiv:2609.30662v1 Announce Type: new Abstract: Large language models (LLMs) can plan, use tools, write code, and execute long-horizon workflows, yet strong local competence does not guarantee project-level...
Original headline: "LLM Parkinsonism: Executive-Control Failure, Token-Inefficient Persistence, and an Uncertainty-Aware Global Executive Control Architecture for Autonomous Language-Model Agents"