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Over-eagerly adapting VLMs for robot control can actually hurt performance, suggesting the original VLM representation already encodes surprisingly useful action priors.
Stop benchmarking agent components in isolation; AgentSelect lets you train models to recommend *entire* agent configurations based on narrative queries.
