# 线性表示假设需要引入群作用：一篇立场论文

- 来源：HuggingFace Daily Papers（社区热门论文）
- 发布时间：2026-09-22 08:00
- AIHOT 分数：35
- AIHOT 链接：https://aihot.news/items/cmufoik6n081cro8wqhxbcfnh
- 原文链接：https://arxiv.org/abs/2609.27158

## AI 摘要

一篇立场论文提出，线性表示假设并非单一假设，而是由表示等价性区分的一族主张，需用群作用形式化表示对象、生成过程与所断言性质。该框架可厘清假设如何随度量、读取点和分析阶段变化，并据此审计常见表示量与近期的可解释性分析。

## 正文

To make claims about representations that generalize beyond a particular trained model, we need to specify when two representations should count as equivalent. The Linear Representation Hypothesis is often discussed without making this equivalence explicit. Different notions of equivalence preserve different structures, so metrics, probes, and interventions that appear to study the same representation may in fact correspond to different hypotheses. We therefore argue that the Linear Representation Hypothesis is not one hypothesis but a family of claims distinguished by representation equivalence. We formalize this idea using group actions, specifying the representation object, the procedure that produces it, and the property ultimately asserted, while accounting for equivalences imposed by the model architecture. This framework clarifies how assumptions can change across metrics, reading points, and analysis stages, and we use it to audit common representation quantities and recent interpretability analyses.