46 lines
1.3 KiB
Markdown
46 lines
1.3 KiB
Markdown
---
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title: "Rubric Aggregation"
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created: 2026-06-27
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updated: 2026-06-27
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type: concept
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tags:
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- rubric
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- evaluation
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- scoring
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sources:
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- "rubrics-survey-2026"
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---
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# Rubric Aggregation
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## 定义
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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。
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## 三类聚合策略
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### 1. 直接平均/求和 (Direct Averaging/Summation)
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所有 rubric items 等权重,直接加总或平均:
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- S_avg = (1/k) Σ cⱼ
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- S_sum = Σ cⱼ
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- 最简单透明,适用于所有 items 同等重要时
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### 2. 加权求和 (Weighted Summation)
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不同 items 赋予不同权重:
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- S_R = Σ wⱼcⱼ / Σ wⱼ
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- 允许关键维度(如 safety、task completion)权重更高
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- 最灵活,但是权重设计本身成为新的设计挑战
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### 3. 隐式聚合 (Implicit Aggregation)
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将完整 rubric + 模型输出直接交给 judge model,让它隐式输出总分:
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- S_imp = f_ϕ(x, y, R)
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- 推理时更简单、成本更低,但不再能观察到每个 item 的贡献
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### 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。
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## 参考
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- [[rubrics-for-llms|Rubrics for LLMs]]
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- [[rubrics-survey-2026|Rubrics Survey (2026)]]
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- [[rubric-driven-evaluation]]
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