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---
title: "Rubric Aggregation"
created: 2026-06-27
updated: 2026-06-27
type: concept
tags:
- rubric
- evaluation
- scoring
sources:
- "rubrics-survey-2026"
---
# Rubric Aggregation
## 定义
Rubric aggregation 指将多个 rubric item 的逐项评分**合并为单一总分**的方法。这是 rubric 评估流水线中 form item scores → overall score 的关键步骤。
## 三类聚合策略
### 1. 直接平均/求和 (Direct Averaging/Summation)
所有 rubric items 等权重,直接加总或平均:
- S_avg = (1/k) Σ cⱼ
- S_sum = Σ cⱼ
- 最简单透明,适用于所有 items 同等重要时
### 2. 加权求和 (Weighted Summation)
不同 items 赋予不同权重:
- S_R = Σ wⱼcⱼ / Σ wⱼ
- 允许关键维度(如 safety、task completion权重更高
- 最灵活,但是权重设计本身成为新的设计挑战
### 3. 隐式聚合 (Implicit Aggregation)
将完整 rubric + 模型输出直接交给 judge model让它隐式输出总分
- S_imp = f_ϕ(x, y, R)
- 推理时更简单、成本更低,但不再能观察到每个 item 的贡献
### 本文主要聚焦显式聚合(加权求和/直接平均),因为可检查、可分析。
## 参考
- [[rubrics-for-llms|Rubrics for LLMs]]
- [[rubrics-survey-2026|Rubrics Survey (2026)]]
- [[rubric-driven-evaluation]]