SOURCE-LINKED INTELLIGENCE
Sensory Precision Inference for Multimodal Arbitration under Uncertainty
Autonomous agents operating on multisensory data cannot assume that all sensory modalities remain consistently informative. In real environments, sensory streams are frequently corrupted by noise, missing data, or inter-modal incongruence, requiring adaptive arbitration between competing sensory hypotheses. While active inference provides a principled framework for uncertainty-guided inference, the role of dynamically inferred sensory precision in generative multimodal arbitration under sensory conflict remains comparatively underexplored. We propose a multimodal perceptual inference model in
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- arXiv · AI, language, vision and robotics · 2026-09-14T05:29:46.000Z
First collected: 2026-09-20T11:41:07.830Z. This is not the publication date.