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ML Collective’s ICML Paper: A Probabilistic Interpretation of Transformers

Since their introduction in 2017, transformers have become the go-to machine learning architecture for natural language processing (NLP) and computer vision. Although they have achieved state-of-the-art performance in these fields, the theoretical framework underlying transformers remains relatively underexplored.

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