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Enhancing Assessment of Self-Consistency in LLM Explanations using Perturbation Strength
Prior work has examined the self-consistency of LLM-generated explanations using surface-level perturbation methods. However, the strength of these perturbations is not explicitly measured and controlled. In this work, we propose an LLM-as-a-judge approach to measure perturbation strength in a unifi
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