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Sensory Precision Inference Proposed for Multimodal Arbitration in Agents
A new arXiv preprint introduces a method for autonomous agents to weigh sensory modalities against each other when inputs are noisy, incomplete, or contradictory. The approach infers how reliable each stream is and uses that estimate to arbitrate between modalities rather than assuming all sensors are equally trustworthy. The work targets robustness in real-world environments where sensory data quality varies over time.