The predictor ablation reports that LLM-judge labels improve accuracy by 8.9 points over string-match labels without passages, and adding retrieved passages improves accuracy by a further 15.8 points.

The predictor ablation reports that LLM-judge labels improve accuracy by 8.9 points over string-match labels without passages, and adding retrieved passages improves accuracy by a further 15.8 points. · CiteArk

测量结果

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每行是一项测量，分别显示论文报告、最近可用实测和累计证据状态。
指标与条件	论文报告	最近可用实测	证据判断
labels: string match · passages: excluded	54.7%	—	尚未评估
labels: string match · passages: excluded	0.547 score	—	尚未评估
labels: LLM judge · passages: excluded	63.6%	—	尚未评估
labels: LLM judge · passages: excluded	0.615 score	—	尚未评估
labels: LLM judge · passages: included	79.4%	—	尚未评估
labels: LLM judge · passages: included	0.785 score	—	尚未评估
	8.9 percentage points	—	尚未评估
	15.8 percentage points	—	尚未评估

The predictor ablation reports that LLM-judge labels improve accuracy by 8.9 points over string-match labels without passages, and adding retrieved passages improves accuracy by a further 15.8 points.

报告指标与观测值

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测量结果