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Audio and acceleration modalities can predict physical interactions with surprising accuracy, but the executor's architecture is the true bottleneck in achieving effective multimodal execution.
Prediction objectives shape the physical knowledge embedded in latent representations, revealing that some parameters are only captured under specific forecasting conditions.
Adapters may store less than half the information expected, with their capacity heavily influenced by parameter placement rather than quantity.