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This paper introduces CARGO, a training-free routing framework that uses the local LLM's own inference-time agreement across sampled responses to decide when to offload to a cloud model, enabling controllable collaboration ratios without additional training.
This paper proposes RMemSafe, a reliability-gated extension for continual test-time adaptation that attenuates source anchoring when the frozen source's predictive entropy becomes high, preventing blind anchoring under source collapse. The method achieves state-of-the-art error reduction on the CCC benchmark.