A researcher proposes tensor transformers for interpreting models under 1 billion parameters. These replace MLPs and attention with bilinear variants, enabling full linear algebra use. The researcher's recent paper used generalized cosine similarity on the full tensor transformer, removing irrelevant symmetries.
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