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Shared descriptive patterns in skill libraries can obscure task-relevant signals, but SkillSight reveals and calibrates these biases to boost retrieval accuracy by over 20%.
MLLMs don't fuse vision and language uniformly: targeted interventions guided by layer-wise attention analysis can significantly boost multimodal reasoning without retraining.
