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This work proposes a cerebellum-inspired control framework that combines multiplexed predictive representations with internal feedback that enables accurate online correction despite delayed feedback and significantly accelerates adaptation.
CivBench is presented, an open-source benchmark for evaluating language model agents in long-horizon, tool-mediated environments through the Model Context Protocol (MCP), and two interface-level metrics are introduced that the environment makes measurable: Proactive Monitoring Rate (PMR) and RAG@10, capturing whether c...
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