Emergent Analogical Reasoning in Transformers
Researchers demonstrate that Transformers develop analogical reasoning—the ability to transfer relational patterns across different domains—through two key mechanisms: geometric alignment of structures in embedding space and functor application. This mechanistic understanding bridges cognitive science and neural network architecture, with findings validated across both synthetic tasks and pretrained large language models.