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Perception Score: A Learned Metric for Open-ended Text Generation Evaluation

AAAI 2021 · Large language models › Language, safety and interpretability · approach: Statistical frameworks for LLM evaluation · 13 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Use Perception Score (large) instead of the strongest reported baselinetext-generation evaluation metrics · ROCStoriesPearson correlation with human judgment: 0.638 -> 0.692Helped
Use Perception Score (large) instead of the strongest reported baselinetext-generation evaluation metrics · Large Movie Review ConditionalPearson correlation with human judgment: 0.491 -> 0.494Helped
Use Perception Score (large) instead of the strongest reported baselinetext-generation evaluation metrics · COCO Image CaptionsPearson correlation with human judgment: 0.504 -> 0.578Helped
Use Perception Score (large) instead of the strongest reported baselinetext-generation evaluation metrics · Large Movie Review UnconditionalPearson correlation with human judgment: 0.173 -> 0.249Helped
Add model uncertainty reweighting (ablation)Perception Score (base) · ROCStoriesPearson correlation with human judgment: 0.653 -> 0.671Helped
Add model uncertainty reweighting (ablation)Perception Score (base) · COCO Image CaptionsPearson correlation with human judgment: 0.551 -> 0.563Helped
Add data uncertainty reweighting (ablation)Perception Score (base) · ROCStoriesPearson correlation with human judgment: 0.636 -> 0.671Helped
Add data uncertainty reweighting (ablation)Perception Score (base) · COCO Image CaptionsPearson correlation with human judgment: 0.538 -> 0.563Helped
Use a context-aware learned metric rather than reference-similarity-only scoringPerception Score · ROCStories adversarial endingsscore: 0.3650Helped

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