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related 0.40 — supporting 4 facts
Prompt Sensitivity (PS) is a metric introduced to systematically measure the effect of prompt changes on model hallucinations [1], quantifying variation in hallucination rates across prompt styles [2], and used alongside Model Variability to attribute causes of hallucinations [3][4].
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Survey and analysis of hallucinations in large language models frontiersin.org 4 facts
claimThe authors of the survey introduce 'Prompt Sensitivity (PS)' as a concrete metric designed to systematically measure the effect of prompt changes on model hallucinations.
claimThe authors of the 'Survey and analysis of hallucinations in large language models' define Prompt Sensitivity (PS) and Model Variability (MV) as metrics to quantify the contribution of prompts versus model-internal factors to hallucinations.
referenceHallucinations can be categorized into four attribution types based on Prompt Sensitivity (PS) and Model Variation (MV) scores: Prompt-dominant (high PS, low MV), Model-dominant (low PS, high MV), Mixed-origin (high PS, high MV), and Unclassified/noise (low PS, low MV).
claimPrompt Sensitivity (PS) is a metric that measures the variation in output hallucination rates under different prompt styles for a fixed model, where high PS indicates that hallucinations are primarily prompt-induced.