The New Wave of Sequence Modeling: A Comparative Analysis of State Space Models and Transformers

Introduction: The Shifting Landscape of Sequence Modeling The field of sequence modeling was fundamentally reshaped in 2017 with the introduction of the Transformer architecture. Its core innovation, the self-attention mechanism, Read More …

Linear-Time Sequence Modeling: An In-Depth Analysis of State Space Models and the Mamba Architecture as Alternatives to Quadratic Attention

The Scaling Barrier: Deconstructing the Transformer’s Quadratic Bottleneck The Transformer architecture, introduced in 2017, has become the cornerstone of modern machine learning, particularly in natural language processing.1 Its success is Read More …