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stat.ML2026
Clustering in Deep Stochastic Transformers
Lev Fedorov, Michaël E. Sander, Romuald Elie +2
Transformers have revolutionized deep learning across various domains but understanding the precise token dynamics remains a theoretical challenge. Existing theories of deep Transf…
stat.ML2025
Towards Understanding the Universality of Transformers for Next-Token Prediction
Michael E. Sander, Gabriel Peyré
Causal Transformers are trained to predict the next token for a given context. While it is widely accepted that self-attention is crucial for encoding the causal structure of seque…