# Contextual Memory

Treating model-internal contextual memory as the shared unit of analysis, this survey introduces five dimensions—Memory Representation, Memory Update, Access, Readout, and Integration—and reviews five research lines (Softmax Attention, Sparse Attention, Linear Attention, State Space Models, and Hybrid Architectures), using 59 release-level records across 14 major model lineages and a frozen comparison of 11 high-performing open-weight endpoints through September 22, 2026 to argue that attention design is diversifying rather than converging, with hybridization and cross-layer reuse making network depth a dimension along which contextual memory is organized.

Treating model-internal contextual memory as the shared unit of analysis, this survey introduces five dimensions—Memory Representation, Memory Update, Access, Readout, and Integration—and reviews five research lines (Softmax Attention, Sparse Attention, Linear Attention, State Space Models, and Hybrid Architectures), using 59 release-level records across 14 major model lineages and a frozen comparison of 11 high-performing open-weight endpoints through September 22, 2026 to argue that attention design is diversifying rather than converging, with hybridization and cross-layer reuse making network depth a dimension along which contextual memory is organized.