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This paper diagnoses perceptual-decision misalignment in Omni-LLMs and proposes a training-free inference-time framework called Modality Subspace Activation to mitigate it by dynamically balancing modality strengths.
This paper introduces the Causal Sensitivity Score (CSS), an interventional metric that evaluates whether clinical LLMs and agents appropriately update their recommendations when patient inputs change along clinically meaningful dimensions. It reveals hidden capability profiles not captured by standard coverage-based metrics, exposing safety blind spots and structural responsiveness deficits.