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cs.LG2025★ 1 cited
Eigenvalues as a Metric for Memory Dynamics in Sequence Models
Rahel Rickenbach, Jelena Trisovic, Alexandre Didier +2
While softmax attention drives state-of-the-art performance in sequence modeling, its quadratic complexity motivates linear alternatives such as state space models (SSMs). Structur…
cs.LG2024★ 3 cited
Understanding the differences in Foundation Models: Attention, State Space Models, and Recurrent Neural Networks
Jerome Sieber, Carmen Amo Alonso, Alexandre Didier +2
Softmax attention is the principle backbone of foundation models for various artificial intelligence applications, yet its quadratic complexity in sequence length can limit its inf…