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cs.CL2025
Transformers through the lens of support-preserving maps between measures
Takashi Furuya, Maarten V. de Hoop, Matti Lassas
Transformers are deep architectures that define ``in-context maps'' which enable predicting new tokens based on a given set of tokens (such as a prompt in NLP applications or a set…
cs.CL2024★ 2 cited
Transformers are Universal In-context Learners
Takashi Furuya, Maarten V. de Hoop, Gabriel Peyré
Transformers are deep architectures that define "in-context mappings" which enable predicting new tokens based on a given set of tokens (such as a prompt in NLP applications or a s…