A Survey on the Linear Representation Hypothesis
The term "linear representation hypothesis" (LRH) has appeared across diverse subfields of artificial intelligence, neuroscience, and cognitive science. But previous works have not consistently treated the LRH as a falsifiable scientific hypothesis; we analyze these inconsistencies and examine their implications for how prior theoretical and methodological results should be interpreted. Based on this analysis, we argue that claims regarding linear representations become well-defined only through careful examination of the model, representation location, feature definition, and evaluation dataset. We therefore propose a more rigorous formalization of the LRH that makes these dependencies e...
| Authors | Sewoong Lee, Marc E. Canby, Ikhyun Cho et al. |
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| Primary category | cs.AI |
| Published | 19 September 2026 |
| Last updated at source | 19 September 2026 |
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